Monitoring Forest Change in Landscapes Under-Going Rapid Energy Development: Challenges and New Perspectives

The accelerated development of energy resources around the world has substantially increased forest change related to oil and gas activities. In some cases, oil and gas activities are the primary catalyst of land-use change in forested landscapes. We discuss the challenges associated with characterizing ecological change related to energy resource development using North America as an exemplar. We synthesize the major impacts of energy development to forested ecosystems and offer new perspectives on how to detect and monitor anthropogenic disturbance during the Anthropocene. The disturbance of North American forests for energy development has resulted in persistent linear corridors, suppression of historical disturbance regimes, novel ecosystems, and the eradication of ecological memory. Characterizing anthropogenic disturbances using conventional patch-based disturbance measures will tend to underestimate the ecological impacts of energy development. Suitable indicators of anthropogenic impacts in forests should be derived from the integration of multi-scalar Earth observations. Relating these indicators to ecosystem condition will be a capstone in the progress toward monitoring forest change in landscapes undergoing rapid energy development.Forestry, Faculty ofNon UBCForest and Conservation Sciences, Department ofForest Resources Management, Department ofReviewedFacult

Confirmation of post-harvest spectral recovery from Landsat time series using measures of forest cover and height derived from airborne laser scanning data

Landsat time series (LTS) enable the characterization of forest recovery post-disturbance over large areas; however, there is a gap in our current knowledge concerning the linkage between spectral measures of recovery derived from LTS and actual manifestations of forest structure in regenerating stands. Airborne laser scanning (ALS) data provide useful measures of forest structure that can be used to corroborate spectral measures of forest recovery. The objective of this study was to evaluate the utility of a spectral index of recovery based on the Normalized Burn Ratio (NBR): the years to recovery, or Y2R metric, as an indicator of the return of forest vegetation following forest harvest (clearcutting). The Y2R metric has previously been defined as the number of years required for a pixel to return to 80% of its pre-disturbance NBR (NBRpre) value. In this study, the Composite2Change (C2C) algorithm was used to generate a time series of gap-free, cloud-free Landsat surface reflectance composites (1985–2012), associated change metrics, and a spatially-explicit dataset of detected changes for an actively managed forest area in southern Finland (5.3 Mha). The overall accuracy of change detection, determined using independent validation data, was 89%. Areas of forest harvesting in 1991 were then used to evaluate the Y2R metric. Four alternative recovery scenarios were evaluated, representing variations in the spectral threshold used to define Y2R: 60%, 80%, and 100% of NBRpre, and a critical value of z (i.e. the year in which the pixel's NBR value is no longer significantly different from NBRpre). The Y2R for each scenario were classified into five groups: recovery within 17 years, and not recovered. Measures of forest structure (canopy height and cover) were obtained from ALS data. Benchmarks for height (>5 m) and canopy cover (>10%) were applied to each recovery scenario, and the percentage of pixels that attained both of these benchmarks for each recovery group, was determined for each Y2R scenario. Our results indicated that the Y2R metric using the 80% threshold provided the most realistic assessment of forest recovery: all pixels considered in our analysis were spectrally recovered within the analysis period, with 88.88% of recovered pixels attaining the benchmarks for both cover and height. Moreover, false positives (pixels that had recovered spectrally, but not structurally) and false negatives (pixels that had recovered structurally, but not spectrally) were minimized with the 80% threshold. This research demonstrates the efficacy of LTS-derived assessments of recovery, which can be spatially exhaustive and retrospective, providing important baseline data for forest monitoring.Peer reviewe

Monitoring anthropogenic disturbance trends in an industrialized boreal forest with Landsat time series

Human transformation of the terrestrial biosphere via resource utilization is a critical impetus for monitoring and characterizing anthropogenic change to vegetation condition. The primary objective of this research was to detect anthropogenic forest disturbance for a recent Landsat time series. A novel combination of an autonomous change detection procedure and spectral classification scheme was applied and tested in a landscape that has undergone significant resource development over the last 30 years. Anthropogenic disturbance was detected with greater than 93% accuracy. Most disturbances were correctly classified to within ±1 year. The signal of anthropogenic disturbance was significant in the landscape, accounting for more than 91% of all disturbances and 86% of total disturbed area during the 23-year study period. The study demonstrated a robust approach for examining historical disturbance trends related to human-modification of the environment.Forestry, Faculty ofNon UBCForest Resources Management, Department ofReviewedFacultyResearcherPostdoctora

Evolution of Canada's Boreal Forest Spatial Patterns as Seen from Space.

Understanding the development of landscape patterns over broad spatial and temporal scales is a major contribution to ecological sciences and is a critical area of research for forested land management. Boreal forests represent an excellent case study for such research because these forests have undergone significant changes over recent decades. We analyzed the temporal trends of four widely-used landscape pattern indices for boreal forests of Canada: forest cover, largest forest patch index, forest edge density, and core (interior) forest cover. The indices were computed over landscape extents ranging from 5,000 ha (n = 18,185) to 50,000 ha (n = 1,662) and across nine major ecozones of Canada. We used 26 years of Landsat satellite imagery to derive annualized trends of the landscape pattern indices. The largest declines in forest cover, largest forest patch index, and core forest cover were observed in the Boreal Shield, Boreal Plain, and Boreal Cordillera ecozones. Forest edge density increased at all landscape extents for all ecozones. Rapidly changing landscapes, defined as the 90th percentile of forest cover change, were among the most forested initially and were characterized by four times greater decrease in largest forest patch index, three times greater increase in forest edge density, and four times greater decrease in core forest cover compared with all 50,000 ha landscapes. Moreover, approximately 18% of all 50,000 ha landscapes did not change due to a lack of disturbance. The pattern database results provide important context for forest management agencies committed to implementing ecosystem-based management strategies

Temporal correlograms of forest cover observed for the 50,000 ha landscape extent.

<p>Each boxplot has <i>n</i> = 1,662 landscapes and represents the distribution of autocorrelation values at each lag. Solid red line is correlation = 0. Dashed red lines represent ±2 standard errors of the mean correlation value (<i>i</i>.<i>e</i>., 95% confidence bounds). Lags with interquartile range outside ±2 standard errors are considered significant for all 50,000 ha landscapes.</p

Sample of Landsat tiles distributed across major ecozones of Canada [57].

<p>Sample of Landsat tiles distributed across major ecozones of Canada [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0157736#pone.0157736.ref057" target="_blank">57</a>].</p

Median Theil-Sen slope of largest forest patch index from 1985 to 2010 for each ecozone and landscape extent.

<p>Error bars indicate the upper and lower 95% confidence bounds. Asterisks (*) indicate significant (p < 0.05) monotonic trends from a Mann-Kendall test.</p

Heat-map scatterplots showing the relationships between the four landscape pattern indices in 2010 for the 5,000 ha landscapes (<i>n</i> = 18,185).

<p>Heat-map scatterplots showing the relationships between the four landscape pattern indices in 2010 for the 5,000 ha landscapes (<i>n</i> = 18,185).</p

Locations of 50,000 ha landscapes classed by landscape magnitude change across the boreal forest zone of Canada.

<p>Locations of 50,000 ha landscapes classed by landscape magnitude change across the boreal forest zone of Canada.</p