Maximum likelihood parametric reconstruction of forest vertical structure from inclined laser quadrat sampling.

Abstract Forest vertical structure is critical to ecological function, and provides a crucial link to air- and spaceborne remote sensing (including LiDAR), but is difficult to measure from the ground. Laser point quadrat sampling has been suggested as one alternative, but previous statistical approaches to modeling forest structure using such data have required impractical sample sizes. Here, I develop the theory for maximum likelihood estimation of a parametric model of forest vertical structure, and illustrate it using inclined point quadrat sampling with a handheld laser. Results from three forest stands in arctic Norway suggest excellent qualitative agreement with structure derived from alternative methods. The approach generalizes readily to other hardware configurations, including terrestrial laser scanning

Potential applications of randomised graph sampling to invasive species surveillance and monitoring.

Abstract Many invasive plants and animals disperse preferentially through linear networks in the landscape, including road networks, riparian corridors, and power transmission lines. Unless the network of interest is small, or the budget for surveillance is large, it may be necessary to draw inferences from a sample rather than a complete census on the network. Desired features of a surveillance system to detect and quantify invasion include: (1) the ability to make unbiased statements about the spatial extent of invasion, the abundance of the invading organism, and the degree of impact; (2) the ability to quantify the uncertainty associated with those statements; (3) the ability to sample by moving within the network in a reasonable fashion, and with little wasted non-measurement time; and (4) the ability to incorporate auxiliary information (such as remotely sensed data, ecological models, or expert opinion) to direct sampling where it will be most fruitful. Randomised graph sampling (RGS) has all of these attributes. The network of interest (such as a road network) is recomposed into a graph, consisting of vertices (such as road intersections) and edges (such as road segments connecting nodes). The vertices and edges are used to construct paths representing reasonable sampling routes through the network; these paths are then sampled, potentially with unequal probability. Randomised graph sampling is unbiased, and the incorporation of auxiliary information can dramatically reduce sample variances. We illustrate RGS using simplified examples, and a survey of Polygonum cuspidatum (Siebold & Zucc.) within a high-priority conservation region in southern Maine, USA

Spatial distribution of forest aboveground biomass estimated from remote sensing and forest inventory data in New England, USA.

Abstract We combined satellite (Landsat 7 and Moderate Resolution Imaging Spectrometer) and U.S. Department of Agriculture forest inventory and analysis (FIA) data to estimate forest aboveground biomass (AGB) across New England, USA. This is practical for large-scale carbon studies and may reduce uncertainty of AGB estimates. We estimate that total regional forest AGB was 1,867 teragram (1012, dry weight) in 2001, with a mean AGB density of 120 Mg/ha (Standard deviation = 54 Mg/ha) ranging from 15 to 240 Mg/ha within a 95% percentile. The majority of regional AGB density was in the range of 80 to 160 Mg/ha (58.2%). High AGB densities were observed along the Appalachian Mountains from northwestern Connecticut to the Green Mountains in Vermont and White Mountains in New Hampshire, while low AGB densities were concentrated in the Downeast area of Maine (ME) and the Cape Cod area of Massachusetts (MA). At the state level, the averaged difference in mean AGB densities between simulated and FIA (as reference) was -2.0% ranging from 0% to -4.2% with a standard error of 3.2%. Within the 95% confidence interval the differences between FIA and simulated AGB densities ranged from 0 to 6% (absolute value). Our study may provide useful information for regional fuel-loading estimates

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

Invasion of winter moth in New England: Effects of defoliation and site quality on tree mortality.

Abstract Widespread and prolonged defoliation by the European winter moth, Operophtera brumata L., has occurred in forests of eastern Massachusetts for more than a decade and populations of winter moth continue to invade new areas of New England. This study characterized the forests of eastern Massachusetts invaded by winter moth and related the duration of winter moth defoliation estimated using dendrochronology to observed levels of tree mortality and understory woody plant density. Quercus basal area mortality in mixed Quercus and mixed Quercus-Pinus strobus forests in eastern Massachusetts ranged from 0-30%; mortality of Quercus in these forests was related to site quality and the number of winter moth defoliation events. In addition, winter moth defoliation events lead to a subsequent increase in understory woody plant density. Our results indicate that winter moth defoliation has been an important disturbance in New England forests that may have lasting impacts

Carbon changes in conterminous US forests associated with growth and major disturbances.

Abstract We estimated forest area and carbon changes in the conterminous United States using a remote sensing based land cover change map, forest fire data from the Monitoring Trends in Burn Severity program, and forest growth and harvest data from the USDA Forest Service, Forest Inventory and Analysis Program. Natural and human-associated disturbances reduced the forest ecosystems\u27 carbon sink by 36% from 1992 to 2001, compared to that without disturbances in the 48 states. Among the three identified disturbances, forest-related land cover change contributed 33% of the total effect in reducing the forest carbon potential sink, while harvests and fires accounted for 63% and 4% of the total effect, respectively. The nation\u27s forests sequestered 1.6 ± 0.1Pg (1015 petagram) carbon during the period, or 0.18PgCyr-1, with substantial regional variation. The southern region of the United States was a small net carbon source whereas the greater Pacific Northwest region was a strong net sink. Results of the approach fit reasonably well at an aggregate level with other related estimates of the current forest US greenhouse gas inventory, suggesting that further research using this approach is warranted

Forests in Flux: The Effects of Demographic Change on Forest Cover in New England and New York

This brief contributes to a better understanding of the linkages between demographic and forest cover change so as to inform policy efforts aimed at maintaining existing forested areas in and around sprawling urban centers. Authors Mark Ducey, Kenneth Johnson, Ethan Belair, and Miranda Mockrin report that forest cover has declined throughout New England and New York over the last decade. In rural areas, forest loss is primarily due to commercial timber harvesting and represents a temporary change. Conversely, forest cover decline in urban areas is usually the result of development and is likely to be permanent. Forest cover change is strongly linked to demographic variables throughout this region. Forest cover loss is most pronounced along the urban fringe, where population growth is greatest. Amenity-rich rural areas are also experiencing high rates of population growth and regionally-high rates of forest cover loss. However, the causes of forest cover change in these areas are less certain. Forest cover change has the potential to impact ecosystem services important to both local residents and the larger region

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

Comparison of forest attributes derived from two terrestrial lidar systems.

Abstract Terrestrial lidar (TLS) is an emerging technology for deriving forest attributes, including conventional inventory and canopy characterizations. However, little is known about the influence of scanner specifications on derived forest parameters. We compared two TLS systems at two sites in British Columbia. Common scanning benchmarks and identical algorithms were used to obtain estimates of tree diameter, position, and canopy characteristics. Visualization of range images and point clouds showed clear differences, even though both scanners were relatively high-resolution instruments. These translated into quantifiable differences in impulse penetration, characterization of stems and crowns far from the scan location, and gap fraction. Differences between scanners in estimates of effective plant area index were greater than differences between sites. Both scanners provided a detailed digital model of forest structure, and gross structural characterizations (including crown dimensions and position) were relatively robust; but comparison of canopy density metrics may require consideration of scanner attributes

Carbon benefits from protected areas in the conterminous United States

Background: Conversion of forests to other land cover or land use releases the carbon stored in the forests and reduces carbon sequestration potential of the land. The rate of forest conversion could be reduced by establishing protected areas for biological diversity and other conservation goals. The purpose of this study is to quantify the efficiency and potential of forest land protection for mitigating GHG emissions. Results: The analysis of related national-level datasets shows that during the period of 1992–2001 net forest losses in protected areas were small as compared to those in unprotected areas: -0.74% and −4.07%, respectively. If forest loss rates in protected and unprotected area had been similar, then forest losses in the protected forestlands would be larger by 870 km2/yr forests, that corresponds to release of 7 Tg C/yr (1 Tg=1012 g). Conversely, and continuing to assume no leakage effects or interactions of prices and harvest levels, about 1,200 km2/yr forests could have remained forest during the period of 1992–2001 if net area loss rate in the forestland outside protected areas was reduced by 20%. Not counting carbon in harvested wood products, this is equivalent to reducing fossil-fuel based carbon emissions by 10 Tg C/yr during this period. The South and West had much higher potentials to mitigate GHG emission from reducing loss rates in unprotected forests than that of North region. Spatially, rates of forest loss were higher across the coastal states in the southeastern US than would be expected from their population change, while interior states in the northern US experienced less forest area loss than would have been expected given their demographic characteristics. Conclusions: The estimated carbon benefit from the reduced forest loss based on current protected areas is 7 Tg C/yr, equivalent to the average carbon benefit per year for a previously proposed ten-year $110 million per year tree planting program scenario in the US. If there had been a program that could have reduced forest area loss by 20% in unprotected forestlands during 1992–2001, collectively the benefits from reduced forest loss would be equal to 9.4% of current net forest ecosystem carbon sequestration in the conterminous US