The politics of urban trees: Tree planting is associated with gentrification in Portland, Oregon.

This study evaluated the hypothesis that urban-tree planting increases neighborhood gentrification in Portland, Oregon. We defined gentrification as an increase in the median sales price of single-family homes in a Census tract compared to other tracts in the city after accounting for differences in the housing stock such as house size and number of bathrooms. We used tree-planting data from the non-profit Friends of Trees, who have planted 57,985 yard and street trees in Portland (1990-2019). We estimated a mixed model of gentrification (30 years and 141 tracts) including random intercepts at the tract level and a first-order auto-regressive residual structure. Tract-level house prices and tree planting may be codetermined. Therefore, to address potential endogeneity of tree planting in statistical modeling, we lagged the number of trees planted by at least one year. We found that the number of trees planted in a tract was significantly associated with a higher tract-level median sales price, although it took at least six years for this relationship to emerge. Specifically, each tree was associated with a $131 (95% CI: $53-$210; p-value=0.001) increase in tract-level median sales price six years after planting. The magnitude of the association between the number of trees planted and median sales price generally increased as the time lag lengthened. After twelve years, each tree was associated with a $265 (95% CI: $151-$379; p-value<0.001) increase in tract-level median sales price. Tree planting was not merely a proxy for existing tree cover, as the percent of tract covered in tree canopy was independently associated with an increase in median sales price. Specifically, each 1-percentage point increase in tree-canopy cover was associated with a $882 (95% CI: $226-$1,538; p-value=0.008) increase in median sales price. In conclusion, tree planting is associated with neighborhood-level gentrification, although the magnitude of the association is modest.

Projecting global planted forest area developments and the associated impacts on global forest product markets.

Planted forests are a rising share of total forests globally and an increasingly important source of timber product output, affecting national and global markets. We estimated econometric models of planted forest area by OECD and non-OECD country groups that control for economic, institutional and environmental policies likely to influence future changes in planted forest area. The models are then used to project planted forest area over next 55 years for 180 countries under five alternative scenarios of global socio-economic changes, represented in shared socioeconomic pathways (SSPs), adjunct products emerging from the Fifth Assessment of the Intergovernmental Panel on Climate Change (IPCC). By embedding key features of the SSP projections into a global forest sector model, we evaluate how planted forests lead to different global forest product market outcomes for each SSP, compared to corresponding outcomes where planted forests are not considered separately. Projected global planted forest area in 2070 ranges from 379 million ha (Mha) for SSP3 (a relatively poor and unequal world) to 475 Mha under SSP5 (a relatively wealthier and more equal world), representing respective increases of 46% and 66% compared to 2015. SSPs with the highest planted forest area increases have the lowest product prices (down by 12% by 2070, compared to SSP5 without planted forests) and higher global forest products production and consumption quantities (by as much as 3.3% by 2070, compared to SSP5 without planted forests). However, production does not increase in all countries by similar amounts, due to changes in relative advantages in production brought about by reduced product prices.

The net benefits of human-ignited wildfire forecasting: the case of Tribal land units in the United States.

Research shows that some categories of human-ignited wildfires might be forecastable, due to their temporal clustering, with the possibility that resources could be pre-deployed to help reduce the incidence of such wildfires. We estimated several kinds of incendiary and other human-ignited wildfire forecast models at the weekly time step for tribal land units in the United States, evaluating their forecast skill out of sample. Analyses show that an Autoregressive Conditional Poisson (ACP) model of both incendiary and non-incendiary human-ignited wildfires is more accurate out of sample compared to alternatives, and the simplest of the ACP models performed the best. Additionally, an ensemble of these and simpler, less analytically intensive approaches performed even better. Wildfire hotspot forecast models using all model types were evaluated in a simulation mode to assess the net benefits of forecasts in the context of law enforcement resource reallocations. Our analyses show that such hotspot tools could yield large positive net benefits for the tribes in terms of suppression expenditures averted for incendiary wildfires but that the hotspot tools were less likely to be beneficial for addressing outbreaks of non-incendiary human-ignited wildfires.

The potential use of mass timber in mid-to high-rise construction and the associated carbon benefits in the United States.

Nonresidential and mid- to high-rise multifamily residential structures in the United States currently use little wood per unit floor area installed, because earlier building codes lacked provisions for structural wood use in those types of buildings. However, revisions to the International Building Code allow for increased wood use in the form of mass timber, as structural and fire safety concerns have been addressed through new science-based design standards and through newly specified construction materials and measures. This study used multiple models to describe alternative futures for new construction, mass timber adoption rates, and the associated carbon benefits in higher than three-story buildings in the United States. The use of mass timber, in place of traditional constructions (i.e., structures dominated by concrete and steel), in projected new higher than three-story buildings was shown to provide combined carbon benefits (i.e., global warming mitigation benefits), including avoided embodied carbon emissions due to the substitution of non-wood alternatives and additional biogenic carbon storage in mass timber materials, of between 9.9 and 16.5 million t CO2e/yr spanning 50 years, 2020 to 2070. These carbon benefits equate to 12% to 20% of the total U.S. harvested wood products carbon storage for 2020. Future research is needed to understand how greater mass timber adoption leads to changes in forest product markets, land use, and total forest sector carbon.

Housing starts and the associated wood products carbon storage by county by Shared Socioeconomic Pathway in the United States.

Harvested wood products found in the built environment are an important carbon sink, helping to mitigate climate change, and their trends in use are determined by economic and demographic factors, which vary spatially. Spatially detailed projections of construction and stored carbon are needed for industry and public decision making, including for appreciating trends in values at risk from catastrophic disturbances. We specify econometric models of single-family and multifamily housing starts by U.S. Census Region, design a method for their spatial downscaling to the county level, and project their quantities and carbon content according to the five Shared Socioeconomic Pathways (SSPs). Starts are projected to decline across all scenarios and potentially drop to below housing replacement levels under SSP3 by mid-century. Wood products carbon stored nationally in structures in use and in landfills is projected to grow across all scenarios but with significant spatial heterogeneity related to disparate trends in construction across counties, ranging from strong growth in the urban counties of the coastal South and West to stagnation in rural counties of the Great Plains and the northern Rockies. The estimated average annual carbon stored in wood products used in and discarded from US residential housing units between 2015-2070 ranged from 51 million t CO2e in SSP3 to 85 million t CO2e in SSP5, representing 47% to 78% of total carbon uptake relative to uptake by all wood products in the United States in 2019.

Shortcomings of the normalized difference vegetation index as an exposure metric.

The health benefits of exposure to trees and plants is a rapidly expanding field of study. Research has shown that exposure is associated with improvements in a wide range of health outcomes including cardiovascular disease, birth outcomes, respiratory disease, cancer, mental health and all-cause mortality1. One of the challenges that these studies face is characterizing participants' exposure to trees and plants. A common approach is to use the normalized difference vegetation index, a greenness index typically derived from satellite imagery. Reliance on the normalized difference vegetation index is understandable; for decades, the imagery required to calculate the normalized difference vegetation index has been available for the entire Earth's surface and is updated at regular intervals. However, the normalized difference vegetation index may do a poor job of fully characterizing the human experience of being exposed to trees and plants, because scenes with the same normalized difference vegetation index value can appear different to the human eye. We demonstrate this phenomenon by identifying sites in Portland, Oregon that have the same normalized difference vegetation index value as a large, culturally significant elm tree. These sites are strikingly different aesthetically, suggesting that use of the normalized difference vegetation index may lead to exposure misclassification. Where possible, the normalized difference vegetation index should be supplemented with other exposure metrics.

The association between tree planting and mortality: A natural experiment and cost-benefit analysis.

Several recent longitudinal studies have found that exposure to the natural environment is associated with lower non-accidental mortality. However, most of these studies used the normalized difference vegetation index (NDVI) as an exposure metric; and because NDVI might not be sensitive enough to adequately capture changes in urban vegetation, these studies might lack true longitudinal variation in exposure. Therefore, we used a natural experiment to assess the impact of 30 years of tree planting by the nonprofit Friends of Trees on non-accidental, cardiovascular, lower-respiratory, and accidental mortality in Portland, Oregon (mortality data were provided by the Oregon Health Authority). We estimated autoregressive mixed models of Census-tract level mortality rate (deaths per 100,000 population) associated with trees planted, including a tract-level random effect. All models used data from the American Community Survey to control for year, race, education, income, and age. Each tree planted in the preceding 15 years was associated with significant reductions in non-accidental (-0.21, 95 % CI: -0.30, -0.12) and cardiovascular mortality (-0.066, 95 % CI: -0.11, -0.027). Furthermore, the dose-response association between tree planting and non-accidental mortality increased in magnitude as trees aged and grew. Each tree planted in the preceding 1-5 years was associated with a reduction in mortality rate of -0.154 (95 % CI: -0.323, 0.0146), whereas each tree planted in the last 6-10 and 11-15 years was associated with a reduction in mortality rate of -0.262 (95 % CI: -0.413, -0.110) and -0.306 (95 % CI: -0.527, -0.0841) respectively. Using US EPA estimates of a value of a statistical life, we estimated that planting a tree in each of Portland's 140 Census tracts would generate $14.2 million in annual benefits (95 % CI: $8.0 million to $20.4 million). In contrast, the annual cost of maintaining 140 trees would be $2,716-$13,720.

Spatiotemporal downscaling of global population and income scenarios for the United States.

Downscaled climate projections need to be linked to downscaled projections of population and economic growth to fully develop implications for land, natural resources, and ecosystems for future scenarios. We develop an empirical spatiotemporal approach for jointly projecting population and income at the county scale in the United States that is consistent with neoclassical economic growth theory and overlapping labor markets and that accounts for labor migration and spatial spillovers. Downscaled projections generated for the five Shared Socioeconomic Pathways used to support global scenario analysis generally show growth focused around relatively few centers especially in the southeast and western regions, with some areas in the Midwest and northeast experiencing population declines. Results are consistent with economic growth theory and with historical trends in population change and convergence of per capita personal income across US counties.

Is tree loss associated with cardiovascular-disease risk in the Women's Health Initiative? A natural experiment.

Data from the Women's Health Initiative were used to quantify the relationship between the loss of trees to an invasive forest pest-the emerald ash borer-and cardiovascular disease. We estimated a semi-parametric Cox proportional hazards model of time to cardiovascular disease, adjusting for confounders. We defined the incidence of cardiovascular disease as acute myocardial infarction requiring overnight hospitalization, silent MI determined from serial electrocardiograms, ischemic or hemorrhagic stroke, or death from coronary heart disease. Women living in a county infested with emerald ash borer had an increased risk of cardiovascular disease (HR=1.25, 95% CI: 1.20-1.31).

The relationship between trees and human health: evidence from the spread of the emerald ash borer.

BACKGROUND: Several recent studies have identified a relationship between the natural environment and improved health outcomes. However, for practical reasons, most have been observational, cross-sectional studies. PURPOSE: A natural experiment, which provides stronger evidence of causality, was used to test whether a major change to the natural environment-the loss of 100 million trees to the emerald ash borer, an invasive forest pest-has influenced mortality related to cardiovascular and lower-respiratory diseases. METHODS: Two fixed-effects regression models were used to estimate the relationship between emerald ash borer presence and county-level mortality from 1990 to 2007 in 15 U.S. states, while controlling for a wide range of demographic covariates. Data were collected from 1990 to 2007, and the analyses were conducted in 2011 and 2012. RESULTS: There was an increase in mortality related to cardiovascular and lower-respiratory-tract illness in counties infested with the emerald ash borer. The magnitude of this effect was greater as infestation progressed and in counties with above-average median household income. Across the 15 states in the study area, the borer was associated with an additional 6113 deaths related to illness of the lower respiratory system, and 15,080 cardiovascular-related deaths. CONCLUSIONS: Results suggest that loss of trees to the emerald ash borer increased mortality related to cardiovascular and lower-respiratory-tract illness. This finding adds to the growing evidence that the natural environment provides major public health benefits.