Jeffrey P. Prestemon

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.

The Effect of Trees on Crime in Portland, Oregon

The authors estimate the relationship between trees and three crime aggregates (all crime, violent crime, and property crime) and two individual crimes (burglary and vandalism) in Portland, Oregon. During the study period (2005-2007), 431 crimes were reported at the 2,813 single-family homes in our sample. In general, the authors find that trees in the public right of way are associated with lower crime rates. The relationship between crime and trees on a house’s lot is mixed. Smaller, view-obstructing trees are associated with increased crime, whereas larger trees are associated with reduced crime. The authors speculate that trees may reduce crime by signaling to potential criminals that a house is better cared for and, therefore, subject to more effective authority than a comparable house with fewer trees.

Time to Burn: Modeling Wildland Arson as an Autoregressive Crime Function

Six Poisson autoregressive models of order p[PAR(p)] of daily wildland arson ignition counts are estimated for five locations in Florida (1994–2001). In addition, a fixed effects time-series Poisson model of annual arson counts is estimated for all Florida counties (1995–2001). PAR(p) model estimates reveal highly significant arson ignition autocorrelation, lasting up to eleven days, in addition to seasonality and links to law enforcement, wildland management, historical fire, and weather. The annual fixed effects model replicates many findings of the daily models but also detects the influence of wages and poverty on arson, in ways expected from theory. All findings support an economic model of crime. Copyright 2005, Oxford University Press.

Spatio-temporal analysis of wildfire ignitions in the St Johns River Water Management District, Florida

We analyse the spatio-temporal structure of wildfire ignitions in the St Johns River Water Management District in north-eastern Florida. We show, using tools to analyse point patterns (e.g. the L-function), that wildfire events occur in clusters. Clustering of these events correlates with irregular distribution of fire ignitions, including lightning and human sources, and fuels on the landscape. In addition, we define a relative clustering index that summarizes the amount of clustering over various spatial scales. We carry our analysis in three steps: purely temporal, purely spatial, and spatio-temporal. Our results show that arson and lightning are the leading causes of wildfires in this region and that ignitions by railroad, lightning, and arson are spatially more clustered than ignitions by other accidental causes.

Evaluating Alternative Prescribed Burning Policies to Reduce Net Economic Damages from Wildfire

We estimate a wildfire risk model with a new measure of wildfire output, intensity-weighted risk and use it in Monte Carlo simulations to estimate welfare changes from alternative prescribed burning policies. Using Volusia County, Florida as a case study, an annual prescribed burning rate of 13% of all forest lands maximizes net welfare; ignoring the effects on wildfire intensity may underestimate optimal rates of prescribed burning. Our estimated supply function for prescribed fire services is inelastic, suggesting that increasing contract prescribed fire services on public lands may produce rapidly escalating costs for private landowners and unintended distributional and “leakage” effects.

North American Oriented Strand Board Markets, Arbitrage Activity, and Market Price Dynamics: A Smooth Transition Approach

Price dynamics for North American oriented strand board markets are examined. The role of transactions costs are explored vis-a-vis the law of one price. Nonlinearities induced by unobservable transactions costs are modeled by estimating time-varying smooth transition autoregressions (TV-STARs). Results indicate that nonlinearity and structural change are important features of these markets; price parity relationships implied by economic theory are generally supported by the estimated models. Implications for the efficiency of spatial market linkages and the dynamics associated with price adjustments are also examined. Copyright 2011, Oxford University Press.

The Effect of Newspaper Coverage and Political Pressure on Wildfire Suppression Costs

Controlling wildfire suppression expenditures has become a major public policy concern in the United States. However, most policy remedies have focused on the biophysical determinants of suppression costs: fuel loads and weather, for example. We show that two non-biophysical variables—newspaper coverage and political pressure—have a significant effect on wildfire suppression costs. Hausman tests showed that newspaper coverage and fire size were endogenous, so regression models were estimated using two-stage least squares. We suggest a number of non-biophysical policy remedies that may be able to reduce wildfire suppression expenditures more cost-effectively than traditional biophysical remedies such as fuel management.

Spatial distribution of human-caused forest fires in Galicia (NW Spain).

It is crucial for fire prevention policies to assess the spatial patterns of human-started fires and their relationship with geographical and socioeconomic aspects. This study uses fire reports for the period 1988-2006 in Galicia, Spain, to analyze the spatial distribution of human-induced fire risk attending to causes and underlying motivations associated with fire ignitions. Our results show that there are four distinctive types of municipalities in this region according to the incidence of intentional agricultural-livestock fires, pyromaniacal behavior, negligence, and unknown causes. They highlight that study of the spatial properties of the human causes and motivations of forest fire activity can provide valuable information for detecting the presence of non-random clusters of fires of various causes in particular locations, where fire management planning should be evaluated more in depth.

Forecasting intentional wildfires using temporal and spatiotemporal autocorrelations

We report daily time series models containing both temporal and spatiotemporal lags, which are applied to forecasting intentional wildfires in Galicia, Spain. Models are estimated independently for each of the 19 forest districts in Galicia using a 1999-2003 training dataset and evaluated out-of-sample with a 2004-06 dataset. Poisson autoregressive models of order P - PAR(P) models - significantly out-perform competing alternative models over both in-sample and out-of-sample datasets, reducing out-of-sample root-mean-squared errors by an average of 15%. PAR(P) and static Poisson models included covariates deriving from crime theory, including the temporal and spatiotemporal autoregressive time series components. Estimates indicate highly significant autoregressive components, lasting up to 3 days, and spatiotemporal autoregression, lasting up to 2 days. Models also applied to predict the effect of increased arrest rates for illegal intentional firesetting indicate that the direct long-run effect of an additional firesetting arrest, summed across forest districts in Galicia, is -139.6 intentional wildfires, equivalent to a long-run elasticity of -0.94. Language: en

Forest product trade impacts of an invasive species: modeling structure and intervention trade-offs.

Asian gypsy and nun moth introductions into the United States, possibly arriving on imported Siberian coniferous logs, threaten domestic forests and product markets and could have global market consequences. We simulate, using the Global Forest Products Model (a spatial equilibrium model of the world forest sector), the consequences under current policies of a widespread, successful pest invasion, and of plausible trading partner responses to the successful invasion. We find that trade liberalization would have a negligible effect on U.S. imports of Siberian logs and, consequently, on the risk of a pest invasion. But, if it happened, possibly through trade in other commodities, a successful and widespread pest invasion would have large effects on producers and consumers over the period 2002 to 2030.