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At least 343 records · Page 19

Disturbance-accelerated succession increases the production of a temperate forest

Many secondary deciduous forests of eastern North America are approaching a transition in which maturing early successional tree species are declining, resulting in an uncertain future for these forests’ century-long carbon (C) sink. We initiated the Forest Accelerated Succession Experiment (FASET) at the University of Michigan Biological Station to examine the patterns and mechanisms underlying forest C cycling following the stem-girdling induced mortality of >6,700 early successional Populus spp. (aspen) and Betula papyrifera (paper birch). Since 2008, meteorological flux tower-based C cycling observations from the 33-ha treatment forest have been paired with those from a nearby unmanipulated forest. Following over a decade of observations, herein we revisit our core hypothesis: that net ecosystem production (NEP) would increase following the transition to mid-late successional species dominance due to increased canopy structural complexity. Supporting our hypothesis, NEP was stable, briefly declined, and then increased relative to the control in the decade following disturbance; however, increasing NEP was not associated with rising structural complexity but rather the rapid 1-year recovery of total LAI as mid-late successional Acer, Quercus, and Pinus assumed canopy dominance. The transition to mid-late successional species dominance improved carbon-use efficiency (CUE = NEP/gross primary production) as ecosystem respiration declined. Similar soil respiration rates in control and treatment forests, along with species differences in leaf physiology and the rising relative growth rates of mid-late successional species in the treatment forest, suggest changes in aboveground plant respiration and growth, respectively, were primarily responsible for increases in NEP. We conclude that deciduous forests transitioning from early to middle succession are capable of sustained or increased NEP, even when experiencing extensive tree mortality. This adds to mounting evidence that aging deciduous forests in the region will function as C sinks for decades to come.

54 ENVIRONMENTAL SCIENCES↗

Inferring pesticide toxicity to honey bees from a field‐based feeding study using a colony model and Bayesian inference

Abstract Honey bees are crucial pollinators for agricultural crops but are threatened by a multitude of stressors including exposure to pesticides. Linking our understanding of how pesticides affect individual bees to colony‐level responses is challenging because colonies show emergent properties based on complex internal processes and interactions among individual bees. Agent‐based models that simulate honey bee colony dynamics may be a tool for scaling between individual and colony effects of a pesticide. The U.S. Environmental Protection Agency (USEPA) and U.S. Department of Agriculture (USDA) are developing the VarroaPop + Pesticide model, which simulates the dynamics of honey bee colonies and how they respond to multiple stressors, including weather, Varroa mites, and pesticides. To evaluate this model, we used Approximate Bayesian Computation to fit field data from an empirical study where honey bee colonies were fed the insecticide clothianidin. This allowed us to reproduce colony feeding study data by simulating colony demography and mortality from ingestion of contaminated food. We found that VarroaPop + Pesticide was able to fit general trends in colony population size and structure and reproduce colony declines from increasing clothianidin exposure. The model underestimated adverse effects at low exposure (36 µg/kg), however, and overestimated recovery at the highest exposure level (140 µg/kg), for the adult and pupa endpoints, suggesting that mechanisms besides oral toxicity‐induced mortality may have played a role in colony declines. The VarroaPop + Pesticide model estimates an adult oral LD 50 of 18.9 ng/bee (95% CI 10.1–32.6) based on the simulated feeding study data, which falls just above the 95% confidence intervals of values observed in laboratory toxicology studies on individual bees. Overall, our results demonstrate a novel method for analyzing colony‐level data on pesticide effects on bees and making inferences on pesticide toxicity to individual bees.

59 BASIC BIOLOGICAL SCIENCES↗

Human–mouse comparison of the multistage nature of radiation carcinogenesis in a mathematical model

Abstract Mouse models are vital for assessing risk from environmental carcinogens, including ionizing radiation, yet the interspecies difference in the dose response precludes direct application of experimental evidence to humans. Herein, we take a mathematical approach to delineate the mechanism underlying the human–mouse difference in radiation‐related cancer risk. We used a multistage carcinogenesis model assuming a mutational action of radiation to analyze previous data on cancer mortality in the Japanese atomic bomb survivors and in lifespan mouse experiments. Theoretically, the model predicted that exposure will chronologically shift the age‐related increase in cancer risk forward by a period corresponding to the time in which the spontaneous mutational process generates the same mutational burden as that the exposure generates. This model appropriately fitted both human and mouse data and suggested a linear dose response for the time shift. The effect per dose decreased with increasing age at exposure similarly between humans and mice on a per‐lifespan basis (0.72‐ and 0.71‐fold, respectively, for every tenth lifetime). The time shift per dose was larger by two orders of magnitude in humans (7.8 and 0.046 years per Gy for humans and mice, respectively, when exposed at ~35% of their lifetime). The difference was mostly explained by the two orders of magnitude difference in spontaneous somatic mutation rates between the species plus the species‐independent radiation‐induced mutation rate. Thus, the findings delineate the mechanism underlying the interspecies difference in radiation‐associated cancer mortality and may lead to the use of experimental evidence for risk prediction in humans.

Oncology↗

Performance of Subyearling Fall Chinook Salmon Tagged with 8-, 9-, and 12-mm Passive Integrated Transponder Tags in the Snake River

Abstract Inferences based on tagged individuals from a population are limited in part by the minimum size of fish that can be tagged. Smaller tags allow a greater proportion of a population to be represented by tagging and should reduce potential tag effects on fish performance. We evaluated different performance metrics of juvenile fall Chinook Salmon Oncorhynchus tshawytscha tagged with 8-, 9-, and 12-mm PIT tags in the Snake River. We did not find evidence that posttagging mortality of 45–49-mm-FL fish tagged with 8-mm tags was higher than the posttagging mortality of larger fish tagged with 9- and 12-mm tags. The incisions of fish tagged with 8-mm tags using 14-guage needles healed faster than those of fish tagged with larger tags using 12-guage needles. For individuals that received 8-mm tags, growth in length and mass was higher for 45–49-mm fish than for 50–59-mm fish and 60-mm and larger fish. Growth of the larger size-classes (50–59 and ≥60 mm) was also generally higher for those tagged with 8-mm tags compared to those tagged with 9- and 12-mm tags, respectively. There were no strong relationships between tag burden (i.e., tag weight expressed as a percentage of fish weight) at the time of tagging and growth metrics for any tag size or fish size-class. Releases made to compare the detection efficiency of the three tag types in the juvenile fish bypass at Lower Granite Dam, Washington, showed that 99–100% of all fish were detected. Survival of fish from rearing areas to Lower Granite Dam generally increased with fish size and varied by year, but there was no strong evidence of a tag size effect. The 8-mm PIT tag allowed us to represent a larger portion (i.e., 6.2–24.1%) of the subyearling fall Chinook Salmon population in the Snake River without compromising fish performance or detectability at the dam.

Tiffan, Kenneth F.↗

Characteristics of an Introduced Walleye Population with Implications for Suppression

Abstract The management of introduced fishes, including Walleye Sander vitreus, whether for control or enhancement, requires understanding of population dynamics at the invasion front. Walleye recently established in the Pend Oreille basin, Idaho, threaten the existing salmonid-based fish community and associated recreational fishery. Therefore, the objectives of this study were to describe population growth and associated life history characteristics. Walleye were sampled in October of 2011, 2014, and 2017 using a standardized gill netting survey protocol to describe trends in relative abundance and evaluate population dynamics. Relative abundance increased exponentially from 1.4 to 4.3 fish/net over the 6-year monitoring period. This population was characterized by fast somatic growth, robust body condition, and early age at maturity at or near the biological maxima for Walleye. Among the survey years, mean length at age 2 varied for female (359–441 mm) and male (358–426 mm) Walleye and relative weight varied from 91 to 98. The sampled Walleye matured at 1 to 4 years of age, and recruitment became more consistent as abundance increased. These density-dependent metrics suggest that the Walleye population is still at low density relative to carrying capacity. The information that was gained from this study was used to better understand potential risks and guide management decisions related to experimental population suppression that is now underway. Suppression under these conditions must overcome the recruitment capabilities of the population. We conclude that natural mortality is likely regulated by density-dependent processes. Therefore, at current (low) density, fishing mortality may be entirely additive and compensation is unlikely to further complicate management.

Ryan, Robert G.↗

Attaining freshwater and estuarine-water soil saturation in an ecosystem-scale coastal flooding experiment

Abstract Coastal upland forests are facing widespread mortality as sea-level rise accelerates and precipitation and storm regimes change. The loss of coastal forests has significant implications for the coastal carbon cycle; yet, predicting mortality likelihood is difficult due to our limited understanding of disturbance impacts on coastal forests. The manipulative, ecosystem-scale Terrestrial Ecosystem Manipulation to Probe the Effects of Storm Treatments (TEMPEST) experiment addresses the potential for freshwater and estuarine-water disturbance events to alter tree function, species composition, and ecosystem processes in a deciduous coastal forest in MD, USA. The experiment uses a large-unit (2000 m 2 ), un-replicated experimental design, with three 50 m × 40 m plots serving as control, freshwater, and estuarine-water treatments. Transient saturation (5 h) of the entire soil rooting zone (0–30 cm) across a 2000 m 2 coastal forest was attained by delivering 300 m 3 of water through a spatially distributed irrigation network at a rate just above the soil infiltration rate. Our water delivery approach also elevated the water table (typically ~ 2 m belowground) and achieved extensive, low-level inundation (~ 8 cm standing water). A TEMPEST simulation approximated a 15-cm rainfall event and based on historic records, was of comparable intensity to a 10-year storm for the area. This characterization was supported by showing that Hurricane Ida’s (~ 5 cm rainfall) hydrologic impacts were shorter (40% lower duration) and less expansive (80% less coverage) than those generated through experimental manipulation. Future work will apply TEMPEST treatments to evaluate coastal forest resilience to changing hydrologic disturbance regimes and identify conditions that initiate ecosystem state transitions.

54 ENVIRONMENTAL SCIENCES↗

Effect of radiation exposure on survival after first solid cancer diagnosis in A-bomb survivors

Comparison of the estimated effect of atomic bomb radiation exposure on solid cancer incidence and solid cancer mortality in the RERF Life Span Study (LSS) reveals a difference in the magnitude and shape of the excess relative risk dose response. A possible contributing factor to this difference is pre-diagnosis radiation effect on post-diagnosis survival. Pre-diagnosis radiation exposure theoretically could influence post-diagnosis survival by affecting the genetic makeup and possibly aggressiveness of cancer, or by compromising tolerance for aggressive treatment for cancer. We analyze the radiation effect on post-diagnosis survival in 20,463 LSS subjects diagnosed with first-primary solid cancer between 1958 and 2009 with particular attention to whether death was caused by the first-primary cancer, other cancer, or non-cancer diseases. From multivariable Cox regression analysis of cause-specific survival, the excess hazard at 1 Gy (EH 1Gy ) for death from the first primary cancer was not significantly different from zero – p = 0.23, EH 1Gy = 0.038 (95 % CI: –0.023, 0.104). Death from other cancer and death from non-cancer diseases both were significantly associated with radiation dose: other cancer EH 1Gy = 0.38 (95 % CI: 0.24, 0.53); non-cancer EH 1Gy = 0.24 (95 % CI: 0.13, 0.36), both p < 0.001. There is no detectable large effect of pre-diagnosis radiation exposure on post-diagnosis death from the first primary cancer in A-bomb survivors. A direct effect of pre-diagnosis radiation exposure on cancer prognosis is ruled out as an explanation for the difference in incidence and mortality dose response in A-bomb survivors.

60 APPLIED LIFE SCIENCES↗

Health co-benefits and mitigation costs as per the Paris Agreement under different technological pathways for energy supply

This study assesses the reductions in air pollution emissions and subsequent beneficial health effects from different global mitigation pathways consistent with the 2 °C stabilization objective of the Paris Agreement. We use an integrated modelling framework, demonstrating the need for models with an appropriate level of technology detail for an accurate co-benefit assessment. The framework combines an integrated assessment model (GCAM) with an air quality model (TM5-FASST) to obtain estimates of premature mortality and then assesses their economic cost. The results show that significant co-benefits can be found for a range of technological options, such as introducing a limitation on bioenergy, carbon capture and storage (CCS) or nuclear power. Cumulative premature mortality may be reduced by 17–23% by 2020–2050 compared to the baseline, depending on the scenarios. However, the ratio of health co-benefits to mitigation costs varies substantially, ranging from 1.45 when a bioenergy limitation is set to 2.19 when all technologies are available. As for regional disaggregation, some regions, such as India and China, obtain far greater co-benefits than others.

54 ENVIRONMENTAL SCIENCES↗

Bark beetle impacts on forest evapotranspiration and its partitioning

Insect outbreaks affect forest structure and function and represent a major category of forest disturbance globally. However, the resulting impacts on evapotranspiration (ET), and especially hydrological partitioning between the abiotic (evaporation) and biotic (transpiration) components of total ET, are not well constrained. As a result, we combined remote sensing, eddy covariance, and hydrological modeling approaches to determine the effects of bark beetle outbreak on ET and its partitioning at multiple scales throughout the Southern Rocky Mountain Ecoregion (SRME), USA. At the eddy covariance measurement scale, 85 % of the forest was affected by beetles, and water year ET as a fraction of precipitation (P) decreased by 30 % relative to a control site, with 31 % greater reductions in growing season transpiration relative to total ET. At the ecoregion scale, satellite remote sensing masked to areas of >80 % tree mortality showed corresponding ET/P reductions of 9–15 % that occurred 6–8 years post-disturbance, and indicated that the majority of the total reduction occurred during the growing season; the Variable Infiltration Capacity hydrological model showed an associated 9–18 % increase in the ecoregion runoff ratio. Long-term (16–18 year) ET and vegetation mortality datasets extend the length of previously published analyses and allowed for clear characterization of the forest recovery period. During that time, transpiration recovery outpaced total ET recovery, which was lagged in part due to persistently reduced winter sublimation, and there was associated evidence of increasing late summer vegetation moisture stress. Overall, comparison of three independent methods and two partitioning approaches demonstrated a net negative impact of bark beetles on ET, and a relatively greater negative impact on transpiration, following bark beetle outbreak in the SRME.

54 ENVIRONMENTAL SCIENCES↗

Climate Drives Modeled Forest Carbon Cycling Resistance and Resilience in the Upper Great Lakes Region, USA

Forests dominate the global terrestrial carbon budget, but their ability to continue doing so in the face of a changing climate is uncertain. A key uncertainty is how forests will respond (resistance) and recover from (resilience) to rising levels of disturbance of varying intensities. This knowledge gap can optimally be addressed by integrating manipulative field experiments with ecophysiological modeling. We used the ED-2.2 model to project carbon fluxes for a northern temperate deciduous forest subjected to a real-world disturbance severity manipulation experiment. ED-2.2 was run for 150 years, starting from near bare ground in 1900, and subjected to three disturbance treatments under an ensemble of climate conditions. Both disturbance severity and climate strongly affected carbon fluxes, and interacted with one another. We then calculated metrics of functional ecosystem stability. Modeled gross primary production exhibited a mean resistance of -0.13, -0.23, and -0.42 (unitless) in response to increasing disturbance severity of 45%, 65%, and 85% mortality, respectively; and resilience of 0.002, 0.004, 0.008 (yr-1) respectively. This pattern held true for other carbon fluxes, meaning that in general simulated GPP declined more initially but recovered more quickly from higher mortality. Notably, however, heterotrophic respiration responded more slowly to disturbance, and its highly variable response was affected by different drivers. This work provides insight into how future conditions might affect the functional stability of mature forests in this region under ongoing climate change and changing disturbance regimes.

54 ENVIRONMENTAL SCIENCES↗

Large Divergence of Projected High Latitude Vegetation Composition and Productivity Due To Functional Trait Uncertainty

Abstract Vegetation distribution and composition are expected to change in northern high latitudes under rapid warming, which regulates ecosystem functions but remains challenging to predict. Vegetation change arises from the interplay of chronic climate trends such as warming and transient demographic processes of recruitment, growth, competition, and mortality. Most predictive models overlooked the role of demographic dynamics controlled by plant traits. Here, we simulate vegetation dynamics at the Kougarok Hillslope site in Alaska under historical and future climates using the E3SM Land Model coupled to the Functionally Assembled Terrestrial Simulator (ELM‐FATES). To evaluate the roles of plant traits, we parameterize the model with 5,265 trait configurations representing diverse physiological and demographic strategies. Results show current modeled biomass, composition, and productivity are most sensitive to traits controlling photosynthetic capacity, carbon allocation, allometry, and phenology. Among all trait configurations, ∼5% reproduce in situ biomass and plant functional type (PFT) composition measured in 2016, that are indistinguishable from these two observed ecosystem states. Notably, these same trait configurations produce diverging biomass, composition, and productivity under future climate, where the uncertainty attributable to traits is twice the change attributable to climate change. The variation of projected productivity arises from emerging PFT composition under novel climate regimes, primarily explained by traits controlling cold‐induced mortality, recruitment, and allometry. Our findings highlight the importance and uncertainty of demographic dynamics and its interaction with climate change in shaping Arctic vegetation change. Improved model predictions will likely benefit from explicit consideration of vegetation demography and better constraints of critical traits.

54 ENVIRONMENTAL SCIENCES↗

Representing Soil Microbial Dynamics and Organo‐Mineral Interactions in the E3SM Land Model (ELM‐ReSOM)

Explicit representation of soil microbial processes and interactions with biotic and abiotic processes in Earth System Models (ESMs) remains limited, despite their importance in biogeochemical cycles. To address this gap, which hinders prediction of global biogeochemial cycling and responses to atmospheric conditions, we integrated a microbe- and mineral-surface-explicit model, the Reaction-network-based model of soil organic matter and Microbes (ReSOM), into the Energy Exascale ESM (E3SM) land model (ELM). Here, we describe ELM-ReSOM and show a case study at a conifer forest in California. ELM-ReSOM accurately simulated surface CO 2 fluxes and SOM stocks, demonstrating improved representations of microbial and mineral interactions compared to the default ELM. We examined ELM-ReSOM sensitivity to microbial traits, enzyme properties, and organo-mineral interactions. Microbial traits such as the maximum mortality rate, transporter-density scaling factor, and maximum monomer assimilation rate were strong controllers of heterotrophic respiration, while these microbial traits and enzyme-related properties collectively influenced SOM stocks. Mineral surfaces primarily affected SOM stocks by adsorbing enzymes, thereby limiting depolymerization. Synergies among processes led to stronger impacts of parameters when evaluated together versus separately (i.e., most parameters had greater indirect than direct effects). For example, due to interactions of microbial necromass with mineral surface adsorption, the indirect effect of the maximum microbial mortality rate was 33% larger than its direct effect on SOM stock. Thus, microbial and enzyme dynamics and their interactions with mineral surfaces play critical roles in SOM cycling. Tackling the challenges of microbe-explicit models will advance understanding and modeling of SOM dynamics.

Tao, Jing [Lawrence Berkeley National Laboratory (↗

Investigating Coastal Vegetation Dynamics and Ecosystem Impacts Under Elevated CO 2 and Temperature: A Process‐Based Approach

Coastal forests are increasingly vulnerable to climate change and sea-level rise, with flooding and salinity driving transitions to marsh-dominated ecosystems. Using the coastal version of FATES-Hydro, we conducted 30-year simulations at two coastal forest sites—a broadleaf swamp white oak stand at Lake Erie and a conifer loblolly pine stand at Chesapeake Bay—under historical climate and elevated CO 2 (+100 ppm) and temperature (+1.5°C) scenarios. Elevated CO 2 increased net primary productivity at both sites, while warming alone intensified hydraulic stress and accelerated mortality, particularly in the conifer stand. Simulations show that elevated temperatures intensify vapor pressure deficit and hydraulic stress on trees already experiencing salinity- and submersion-driven water stress, increasing tree mortality beyond what would be expected in a non-water-limited environment. Marsh expansion partially compensated for tree loss at the Lake Erie site but reduced ecosystem productivity in the conifer forest at Chesapeake Bay. In conclusion, our results highlight how differences in stand structure, phenology, and local hydrology modulate ecosystem trajectories under climate change, emphasizing the importance of demographic and community-level processes for predicting the fate of coastal forests.

Ding, Junyan [Barcelona Supercomputing Center (BSC↗

Amazon windthrow disturbances are likely to increase with storm frequency under global warming

Abstract Forest mortality caused by convective storms (windthrow) is a major disturbance in the Amazon. However, the linkage between windthrows at the surface and convective storms in the atmosphere remains unclear. In addition, the current Earth system models (ESMs) lack mechanistic links between convective wind events and tree mortality. Here we find an empirical relationship that maps convective available potential energy, which is well simulated by ESMs, to the spatial pattern of large windthrow events. This relationship builds connections between strong convective storms and forest dynamics in the Amazon. Based on the relationship, our model projects a 51 ± 20% increase in the area favorable to extreme storms, and a 43 ± 17% increase in windthrow density within the Amazon by the end of this century under the high-emission scenario (SSP 585). These results indicate significant changes in tropical forest composition and carbon cycle dynamics under climate change.

54 ENVIRONMENTAL SCIENCES↗

Climate, air quality, and equity benefits from hydrogen substitution for fossil fuels used in process heat

Fossil fuel combustion for process heat in heavy industry accounts for ~15% of all United States CO 2 emissions and emits PM 2.5 and its precursors, emissions that have a disproportionate impact on minority populations. Decarbonizing process heat in the U.S. via hydrogen substitution presents an opportunity to reduce emissions of CO 2 and PM 2.5 and mitigate resulting exposure disparity. Here, we show that hydrogen substitution in steelmaking provides a large reduction in CO 2 emissions and air quality-related premature mortality, while hydrogen substitution in petroleum refining substantially benefits disadvantaged communities. When reductions in CO 2 emissions and premature mortality are monetized using standard regulatory values, we find that the sum of air pollution and climate benefits outweighs the difference in private cost associated with hydrogen substitution in steelmaking, regardless of the method of hydrogen production. The approach developed here can support evaluations of equity-focused decarbonization strategies in other industries and for specific sites.

08 HYDROGEN↗

Viral but not bacterial community successional patterns reflect extreme turnover shortly after rewetting dry soils

As central members of soil trophic networks, viruses have the potential to drive substantial microbial mortality and nutrient turnover. Pinpointing viral contributions to terrestrial ecosystem processes remains a challenge, as temporal dynamics are difficult to unravel in the spatially and physicochemically heterogeneous soil environment. In Mediterranean grasslands, the first rainfall after seasonal drought provides an ecosystem reset, triggering microbial activity during a tractable window for capturing short-term dynamics. In this report we simulated precipitation in microcosms from four distinct dry grassland soils and generated 144 viromes, 84 metagenomes and 84 16S ribosomal RNA gene amplicon datasets to characterize viral, prokaryotic and relic DNA dynamics over 10 days. Vastly different viral communities in each soil followed remarkably similar successional trajectories. Wet-up triggered a significant increase in viral richness, followed by extensive compositional turnover. Temporal succession in prokaryotic communities was much less pronounced, perhaps suggesting differences in the scales of activity captured by viromes (representing recently produced, ephemeral viral particles) and total DNA. Still, differences in the relative abundances of Actinobacteria (enriched in dry soils) and Proteobacteria (enriched in wetted soils) matched those of their predicted phages, indicating viral predation of dominant bacterial taxa. Rewetting also rapidly depleted relic DNA, which subsequently reaccumulated, indicating substantial new microbial mortality in the days after wet-up, particularly of the taxa putatively under phage predation. Production of abundant, diverse viral particles via microbial host cell lysis appears to be a conserved feature of the early response to soil rewetting, and results suggest the potential for ‘Cull-the-Winner’ dynamics, whereby viruses infect and cull but do not decimate dominant host populations.

54 ENVIRONMENTAL SCIENCES↗

Budget constrained machine learning for early prediction of adverse outcomes for COVID-19 patients

Abstract The combination of machine learning (ML) and electronic health records (EHR) data may be able to improve outcomes of hospitalized COVID-19 patients through improved risk stratification and patient outcome prediction. However, in resource constrained environments the clinical utility of such data-driven predictive tools may be limited by the cost or unavailability of certain laboratory tests. We leveraged EHR data to develop an ML-based tool for predicting adverse outcomes that optimizes clinical utility under a given cost structure. We further gained insights into the decision-making process of the ML models through an explainable AI tool. This cohort study was performed using deidentified EHR data from COVID-19 patients from ProMedica Health System in northwest Ohio and southeastern Michigan. We tested the performance of various ML approaches for predicting either increasing ventilatory support or mortality. We performed post hoc analysis to obtain optimal feature sets under various budget constraints. We demonstrate that it is possible to achieve a significant reduction in cost at the expense of a small reduction in predictive performance. For example, when predicting ventilation, it is possible to achieve a 43% reduction in cost with only a 3% reduction in performance. Similarly, when predicting mortality, it is possible to achieve a 50% reduction in cost with only a 1% reduction in performance. This study presents a quick, accurate, and cost-effective method to evaluate risk of deterioration for patients with SARS-CoV-2 infection at the time of clinical evaluation.

97 MATHEMATICS AND COMPUTING↗

Current inequality and future potential of US urban tree cover for reducing heat-related health impacts

Excessive heat is a major and growing risk for urban residents. Here, we estimate the inequality in summertime heat-related mortality, morbidity, and electricity consumption across 5723 US municipalities and other places, housing 180 million people during the 2020 census. On average, trees in majority non-Hispanic white neighborhoods cool the air by 0.19 ± 0.05 °C more than in POC neighborhoods, leading annually to trees in white neighborhoods helping prevent 190 ± 139 more deaths, 30,131 ± 10,406 more doctors’ visits, and 1.4 ± 0.5 terawatt-hours (TWhr) more electricity consumption than in POC neighborhoods. We estimate that an ambitious reforestation program would require 1.2 billion trees and reduce population-weighted average summer temperatures by an additional 0.38 ± 0.01 °C. This temperature reduction would reduce annual heat-related mortality by an additional 464 ± 89 people, annual heat-related morbidity by 80,785 ± 6110 cases, and annual electricity consumption by 4.3 ± 0.2 TWhr, while increasing annual carbon sequestration in trees by 23.7 ± 1.2 MtCO 2 e yr -1 and decreasing annual electricity-related GHG emissions by 2.1 ± 0.2 MtCO 2 e yr -1 . The total economic value of these benefits, including the value of carbon sequestration and avoided emissions, would be USD 9.6 ± 0.5 billion, although in many neighborhoods the cost of planting and maintaining trees to achieve this increased tree cover would exceed these benefits. The exception is areas that currently have less tree cover, often the majority POC, which tend to have a relatively high return on investment from tree planting.

54 ENVIRONMENTAL SCIENCES↗