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The critical role of forests in the global carbon cycle is well known, but significant uncertainties remain about the specific role of disturbance, in part because of the challenge of incorporating spatial and temporal detail in the characterization of disturbance processes. In this study, we link forest inventory data to remote sensing data to derive estimates of pre- and post-disturbance biomass, and then use near-annual remote sensing observations of forest disturbance to characterize biomass loss associated with disturbance across the conterminous U.S. between 1986 and 2004. Nationally, year-to-year variability in the amount of live aboveground carbon lost as a result of disturbance ranged from a low of 61 Tg C (±16) in 1991 to a high of 84 Tg C (±33) in 2003. Eastern and western forest strata were relatively balanced in terms of their proportional contribution to national-level trends, despite eastern forests having more than twice the area of western forests. In the eastern forest stratum, annual biomass loss tracked closely with the area of disturbance, whereas in the western forest stratum, annual biomass loss showed more year-to-year variability that did not directly correspond to the area of disturbance, suggesting that the biomass density of forests affected by disturbance in the west was more spatially and temporally variable. Eastern and western forest strata exhibited somewhat opposing trends in biomass loss, potentially corresponding to the implementation of the Northwest Forest Plan in the mid 1990s that resulted in a shift of timber harvesting from public lands in the northwest to private lands in the south. Overall, these observations document modest increases in disturbance rates and associated carbon consequences over the 18-year period. These changes are likely not significant enough to weaken a growing forest carbon sink in the conterminous U.S. based largely on increased forest growth rates and biomass densities.

Interest in preserving older forests at the landscape level has increased in many regions, including the Pacific Northwest of the United States. The Northwest Forest Plan (NWFP) of 1994 initiated a significant reduction in the harvesting of older forests on federal land. We used historical satellite imagery to assess the effect of this reduction in relation to: past harvest rates, management of non-federal forests, and the growing role of fire. Harvest rates in non-federal large-diameter forests (LDF) either decreased or remained stable at relatively high rates following the NWFP, meaning that harvest reductions on federal forests, which cover half of the region, resulted in a significant regional drop in the loss of LDF to harvest. However, increased losses of LDF to fire outweighed reductions in LDF harvest across large areas of the region. Elevated fire levels in the western United States have been correlated to changing climatic conditions, and if recent fire patterns persist, preservation of older forests in dry ecosystems will depend upon practical and coordinated fire management across the landscape.

Although habitat fragmentation is one of the greatest threats to biodiversity worldwide, virtually no attention has been paid to the quantification of error in fragmentation statistics. Landscape pattern indices (LPIs), such as mean patch size and number of patches, are routinely used to quantify fragmentation and are often calculated using remote-sensing imagery that has been classified into different land-cover classes. No classified map is ever completely correct, so we asked if different maps with similar misclassification rates could result in widely different errors in pattern indices. We simulated landscapes with varying proportions of habitat and clumpiness (autocorrelation) and then simulated classification errors on the same maps. We simulated higher misclassification at patch edges (as is often observed), and then used a smoothing algorithm routinely used on images to correct salt-and-pepper classification error. We determined how well classification errors (and smoothing) corresponded to errors seen in four pattern indices. Maps with low misclassification rates often yielded errors in LPIs of much larger magnitude and substantial variability. Although smoothing usually improved classification error, it sometimes increased LPI error and reversed the direction of error in LPIs introduced by misclassification. Our results show that classification error is not always a good predictor of errors in LPIs, and some types of image postprocessing (for example, smoothing) might result in the underestimation of habitat fragmentation. Furthermore, our results suggest that there is potential for large errors in nearly every landscape pattern analysis ever published, because virtually none quantify the errors in LPIs themselves.

Ecosystem structure and function are strongly affected by disturbance events, many of which in North America are associated with seasonal temperature extremes, wildfires, and tropical storms. This study was conducted to evaluate patterns in a 19-year record of global satellite observations of vegetation phenology from the advanced very high resolution radiometer (AVHRR) as a means to characterize major ecosystem disturbance events and regimes. The fraction absorbed of photosynthetically active radiation (FPAR) by vegetation canopies worldwide has been computed at a monthly time interval from 1982 to 2000 and gridded at a spatial resolution of 8–km globally. Potential disturbance events were identified in the FPAR time series by locating anomalously low values (FPAR-LO) that lasted longer than 12 consecutive months at any 8-km pixel. We can find verifiable evidence of numerous disturbance types across North America, including major regional patterns of cold and heat waves, forest fires, tropical storms, and large-scale forest logging. Summed over 19 years, areas potentially influenced by major ecosystem disturbances (one FPAR-LO event over the period 1982–2000) total to more than 766,000 km2. The periods of highest detection frequency were 1987–1989, 1995–1997, and 1999. Sub-continental regions of the Pacific Northwest, Alaska, and Central Canada had the highest proportion (>90%) of FPAR-LO pixels detected in forests, tundra shrublands, and wetland areas. The Great Lakes region showed the highest proportion (39%) of FPAR-LO pixels detected in cropland areas, whereas the western United States showed the highest proportion (16%) of FPAR-LO pixels detected in grassland areas. Based on this analysis, an historical picture is emerging of periodic droughts and heat waves, possibly coupled with herbivorous insect outbreaks, as among the most important causes of ecosystem disturbance in North America.

In western Oregon, forest ecosystem processes are greatly affected by patterns of stand replacement disturbance. A spatially explicit characterization of clear-cut logging and wildfire is a prerequisite to understanding the causes and consequences of disturbance in this region. We analyzed stand replacement disturbance over 4.6 million forested hectares of three major provinces in western Oregon between 1972 and 1995, contrasting the relative amounts of wildfire and harvest in each province and comparing harvest statistics among the dominant land ownership categories. Clear-cut harvest and wildfire occurred over 19.9% and 0.7% of the study area, respectively. The moist Coast Range Province (CRP) was dominated by private industrial (PI) ownerships and had the greatest concentration of cutting. The relatively dry Klamath Mountains Province (KMP) and the climatically moderate Western Cascades Province (WCP) were dominated by public landowners and had lower concentrations of cutting and larger amounts of wildfire than the CRP. Rates of harvest over time generally followed similar trends across landowners; it was lowest in the early 1970s, peaked in the late 1980s and early 1990s, and then decreased to near 1970s levels by the mid-1990s. PI landowners had harvest rates that were about two and one-half times as high as public owners throughout the study period. Public and private nonindustrial (PNI) owners tended to have relatively small cutting units that remained spatially dispersed throughout the study period, whereas the PI owners had larger individual cutting units that tended toward spatial aggregation over time. Comparing the managed disturbance regimes with historical wild disturbance regimes can help us to understand the relative impact of management regimes on ecosystems.