Late-successional and old-growth forests in the northeastern United States: Structure, dynamics, and prospects for restoration.

Abstract Restoration of old-growth forest structure is an emerging silvicultural goal, especially in those regions where old-growth abundance falls below the historic range of variability. However, longitudinal studies of old-growth dynamics that can inform silvicultural and policy options are few. We analyzed the change in structure, including stand density, diameter distribution, and the abundance of large live, standing dead, and downed dead trees on 58 late-successional and old-growth plots in Maine, USA, and compared these to regional data from the U.S. Forest Inventory and Analysis program. Structural dynamics on the late-successional plots reflected orderly change associated with density-dependent growth and mortality, but dynamics on the old-growth plots were more variable. Some plots experienced heavy mortality associated with beech bark disease. Diameter distributions conformed poorly to a classic exponential distribution, and did not converge toward such a distribution at the plot scale. Although large live trees showed a broad trend of increasing density in regional forests, recent harvesting patterns offset a considerable fraction of those gains, while mean diameter was static and the number of large dead trees was weakly declining. Even though forests of the northeast are aging, changes in silviculture and forest policy are necessary to accelerate restoration of old-growth structure

Quantifying uncertainty in pest risk maps and assessments : adopting a risk-averse decision maker’s perspective

Pest risk maps are important decision support tools when devising strategies to minimize introductions of invasive organisms and mitigate their impacts. When possible management responses to an invader include costly or socially sensitive activities, decision-makers tend to follow a more certain (i.e., risk-averse) course of action. We presented a new mapping technique that assesses pest invasion risk from the perspective of a risk-averse decision maker. We demonstrated the method by evaluating the likelihood that an invasive forest pest will be transported to one of the U.S. states or Canadian provinces in infested firewood by visitors to U.S. federal campgrounds. We tested the impact of the risk aversion assumption using distributions of plausible pest arrival scenarios generated with a geographically explicit model developed from data documenting camper travel across the study area. Next, we prioritized regions of high and low pest arrival risk via application of two stochastic ordering techniques that employed, respectively, first- and second-degree stochastic dominance rules, the latter of which incorporated the notion of risk aversion. We then identified regions in the study area where the pest risk value changed considerably after incorporating risk aversion. While both methods identified similar areas of highest and lowest risk, they differed in how they demarcated moderate-risk areas. In general, the second-order stochastic dominance method assigned lower risk rankings to moderate-risk areas. Overall, this new method offers a better strategy to deal with the uncertainty typically associated with risk assessments and provides a tractable way to incorporate decisionmaking preferences into final risk estimates, and thus helps to better align these estimates with particular decision-making scenarios about a pest organism of concern. Incorporation of risk aversion also helps prioritize the set of locations to target for inspections and outreach activities, which can be costly. Our results are especially important and useful given the huge number of camping trips that occur each year in the United States and Canada

Quantifying uncertainty in pest risk maps and assessments : adopting a risk-averse decision maker’s perspective

Pest risk maps are important decision support tools when devising strategies to minimize introductions of invasive organisms and mitigate their impacts. When possible management responses to an invader include costly or socially sensitive activities, decision-makers tend to follow a more certain (i.e., risk-averse) course of action. We presented a new mapping technique that assesses pest invasion risk from the perspective of a risk-averse decision maker. We demonstrated the method by evaluating the likelihood that an invasive forest pest will be transported to one of the U.S. states or Canadian provinces in infested firewood by visitors to U.S. federal campgrounds. We tested the impact of the risk aversion assumption using distributions of plausible pest arrival scenarios generated with a geographically explicit model developed from data documenting camper travel across the study area. Next, we prioritized regions of high and low pest arrival risk via application of two stochastic ordering techniques that employed, respectively, first- and second-degree stochastic dominance rules, the latter of which incorporated the notion of risk aversion. We then identified regions in the study area where the pest risk value changed considerably after incorporating risk aversion. While both methods identified similar areas of highest and lowest risk, they differed in how they demarcated moderate-risk areas. In general, the second-order stochastic dominance method assigned lower risk rankings to moderate-risk areas. Overall, this new method offers a better strategy to deal with the uncertainty typically associated with risk assessments and provides a tractable way to incorporate decisionmaking preferences into final risk estimates, and thus helps to better align these estimates with particular decision-making scenarios about a pest organism of concern. Incorporation of risk aversion also helps prioritize the set of locations to target for inspections and outreach activities, which can be costly. Our results are especially important and useful given the huge number of camping trips that occur each year in the United States and Canada

Forest management and wildfire risk in inland northwest

This brief reports the results of a mail survey of forest landowners in northeastern Oregon conducted in the fall of 2012 by the Communities and Forests in Oregon (CAFOR) Project at the University of Colorado and the University of New Hampshire in cooperation with Oregon State University College of Forestry Extension. The mail survey--a follow-up to a telephone survey conducted for the counties of Baker, Union, and Wallowa in the fall of 2011 -was administered to understand who constituted forest landowners in these three coun¬ties and their perceptions about forest management on both public and private land, as well as risks to forests in the area and the actions they have taken to reduce those risks. The respondents indicated that they perceive wildfire as the greatest threat to their lands, and they consider cooperation with neighbors as very or extremely important for land management. Forest landowners believe public lands are managed poorly and see a greater risk of wildfire occurring on neighboring public land than on their own land. Their opinions on land management are not strongly related to background factors or ideology (for example, gender, age, political party, wealth) but may be heavily influenced by personal experience with wildfire

Rapid Assessment of Relative Density in Mixed-Species Stands of the Northeastern United States

Basal area has shortcomings as a measure of stand density, but it is often preferred for operational assessments because it is easy to measure. Previous work has demonstrated that an additive version of Reineke's stand density index can be estimated by a simple tree count using a modified horizontal point sampling technique. We show that this technique can be extended further to estimate a mixed-species density measure that has been developed for complex stands in the northeastern United States, using wood specific gravity to harmonize the density contributions of different species. The sampling technique provides design-unbiased estimates of stand density from a weighted tree count, where the weights depend on specific gravity but not on diameter. Rounding the specific gravity values for different species in the calculation of estimates introduces a trivial amount of bias but streamlines the procedure for rapid use in the field

Use of waveform lidar and hyperspectral sensors to assess selected spatial and structural patterns associated with recent and repeat disturbance and the abundance of sugar maple (Acer saccharum Marsh.) in a temperate mixed hardwood and conifer forest.

Abstract Waveform lidar imagery was acquired on September 26, 1999 over the Bartlett Experimental Forest (BEF) in New Hampshire (USA) using NASA\u27s Laser Vegetation Imaging Sensor (LVIS). This flight occurred 20 months after an ice storm damaged millions of hectares of forestland in northeastern North America. Lidar measurements of the amplitude and intensity of ground energy returns appeared to readily detect areas of moderate to severe ice storm damage associated with the worst damage. Southern through eastern aspects on side slopes were particularly susceptible to higher levels of damage, in large part overlapping tracts of forest that had suffered the highest levels of wind damage from the 1938 hurricane and containing the highest levels of sugar maple basal area and biomass. The levels of sugar maple abundance were determined through analysis of the 1997 Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) high resolution spectral imagery and inventory of USFS Northern Research Station field plots. We found a relationship between field measurements of stem volume losses and the LVIS metric of mean canopy height (r2 = 0.66; root mean square errors = 5.7 m3/ha, p \u3c 0.0001) in areas that had been subjected to moderate-to-severe ice storm damage, accurately documenting the short-term outcome of a single disturbance event

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