Estimation of Plot-Level Burn Severity Using Terrestrial Laser Scanning

Monitoring wildland fire burn severity is important for assessing ecological outcomes of fire and their spatial patterning as well as guiding efforts to mitigate or restore areas where ecological outcomes are negative. Burn severity mapping products are typically created using satellite reflectance data but must be calibrated to field data to derive meaning. The composite burn index (CBI) is the most widely used field-based method used to calibrate satellite-based burn severity data but important limitations of this approach have yet to be resolved. The objective of this study was focused on predicting CBI from point cloud and visible-spectrum camera (RGB) metrics derived from single-scan terrestrial laser scanning (TLS) datasets to determine the viability of TLS data as an alternative approach to estimating burn severity in the field. In our approach, we considered the predictive potential of post-scan-only metrics, differenced pre- and post-scan metrics, RGB metrics, and all three together to predict CBI and evaluated these with candidate algorithms (i.e., linear model, random forest (RF), and support vector machines (SVM) and two evaluation criteria (R-squared and root mean square error (RMSE)). In congruence with the strata-based observations used to calculate CBI, we evaluated the potential approaches at the strata level and at the plot level using 70 TLS and 10 RGB independent variables that we generated from the field data. Machine learning algorithms successfully predicted total plot CBI and strata-specific CBI; however, the accuracy of predictions varied among strata by algorithm. RGB variables improved predictions when used in conjunction with TLS variables, but alone proved a poor predictor of burn severity below the canopy. Although our study was to predict CBI, our results highlight that TLS-based methods for quantifying burn severity can be an improvement over CBI in many ways because TLS is repeatable, quantitative, faster, requires less field-expertise, and is more flexible to phenological variation and biomass change in the understory where prescribed fire effects are most pronounced. We also point out that TLS data can also be leveraged to inform other monitoring needs beyond those specific to wildland fire, representing additional efficiency in using this approach

Automated Structural-level Alignment of Multi-view TLS and ALS Point Clouds in Forestry

Access to highly detailed models of heterogeneous forests from the near surface to above the tree canopy at varying scales is of increasing demand as it enables more advanced computational tools for analysis, planning, and ecosystem management. LiDAR sensors available through different scanning platforms including terrestrial, mobile and aerial have become established as one of the primary technologies for forest mapping due to their inherited capability to collect direct, precise and rapid 3D information of a scene. However, their scalability to large forest areas is highly dependent upon use of effective and efficient methods of co-registration of multiple scan sources. Surprisingly, work in forestry in GPS denied areas has mostly resorted to methods of co-registration that use reference based targets (e.g., reflective, marked trees), a process far from scalable in practice. In this work, we propose an effective, targetless and fully automatic method based on an incremental co-registration strategy matching and grouping points according to levels of structural complexity. Empirical evidence shows the method's effectiveness in aligning both TLS-to-TLS and TLS-to-ALS scans under a variety of ecosystem conditions including pre/post fire treatment effects, of interest to forest inventory surveyors

Action of earthworms on flint burial – a return to Darwin’s estate

For thirty years, from the early 1840s, Charles Darwin documented the disappearance of flints in the grounds of Down House in Kent, at a location originally known as the “Stony Field”. This site (Great Pucklands Meadow - GPM) was visited in 2007 and an experiment set up in this ungrazed grassland. Locally-sourced flints (either large - 12 cm, or small – 5 cm dia.) were deposited at two densities within sixteen 1 m2 plots in a randomised factorial design. The area selected was distant from public access routes and remained unmown throughout the duration here reported. Fixed point photographs were taken at the outset to enable later photogrammetric analysis. After 6 years, the site was re-examined. The flints had generally been incorporated into the soil. Photographs were re-taken, proportion of buried flints recorded and measurements made of burial depth from a quarter of each plot. Results showed that large flints were more deeply incorporated than smaller (p=0.025), but more of the latter were below the soil surface. A controlled laboratory experiment was also conducted using Aporrectodea longa (the dominant earthworm species in GPM) to assess effects of casting in the absence of other biota. Results suggested that this species has a major influence on flint burial through surface casting. Combined with a long term, but small scale collection of A. longa casts from an area close to GPM, all results were consistent with those provided by Darwin and showed that rate of flint burial was within the range 0.21-0.96 cm y-1

How Landscape Ecology Informs Global Land-Change Science and Policy

Landscape ecology is a discipline that explicitly considers the influence of time and space on the environmental patterns we observe and the processes that create them. Although many of the topics studied in landscape ecology have public policy implications, three are of particular concern: climate change; land use–land cover change (LULCC); and a particular type of LULCC, urbanization. These processes are interrelated, because LULCC is driven by both human activities (e.g., agricultural expansion and urban sprawl) and climate change (e.g., desertification). Climate change, in turn, will affect the way humans use landscapes. Interactions among these drivers of ecosystem change can have destabilizing and accelerating feedback, with consequences for human societies from local to global scales. These challenges require landscape ecologists to engage policymakers and practitioners in seeking long-term solutions, informed by an understanding of opportunities to mitigate the impacts of anthropogenic drivers on ecosystems and adapt to new ecological realities

Interaction Diversity Maintains Resiliency in a Frequently Disturbed Ecosystem

Frequently disturbed ecosystems are characterized by resilience to ecological disturbances. Longleaf pine ecosystems are not only resilient to frequent fire disturbance, but this feature sustains biodiversity. We examined how fire frequency maintains beta diversity of multi-trophic interactions in longleaf pine ecosystems, as this community property provides a measure of functional redundancy of an ecosystem. We found that beta interaction diversity at small local scales is highest in the most frequently burned stands, conferring immediate resiliency to disturbance by fire. Interactions become more specialized and less resilient as fire frequency decreases. Local scale patterns of interaction diversity contribute to broader scale patterns and confer long-term ecosystem resiliency. Such natural disturbances are likely to be important for maintaining regional diversity of interactions for a broad range of ecosystems

Linking complex forest fuel structure and fire behaviour at fine scales

Abstract. Improved fire management of savannas and open woodlands requires better understanding of the fundamental connection between fuel heterogeneity, variation in fire behaviour and the influence of fire variation on vegetation feedbacks. In this study, we introduce a novel approach to predicting fire behaviour at the submetre scale, including measurements of forest understorey fuels using ground-based LIDAR (light detection and ranging) coupled with infrared thermography for recording precise fire temperatures. We used ensemble classification and regression trees to examine the relationships between fuel characteristics and fire temperature dynamics. Fire behaviour was best predicted by characterising fuelbed heterogeneity and continuity across multiple plots of similar fire intensity, where impacts from plot-to-plot variation in fuel, fire and weather did not overwhelm the effects of fuels. The individual plot-level results revealed the significance of specific fuel types (e.g. bare soil, pine leaf litter) as well as the spatial configuration of fire. This was the first known study to link the importance of fuelbed continuity and the heterogeneity associated with fuel types to fire behaviour at metre to submetre scales and provides the next step in understanding the complex responses of vegetation to fire behaviour

Integrating plant physiology into simulation of fire behavior and effects

Wildfires are a global crisis, but current fire models fail to capture vegetation response to changing climate. With drought and elevated temperature increasing the importance of vegetation dynamics to fire behavior, and the advent of next generation models capable of capturing increasingly complex physical processes, we provide a renewed focus on representation of woody vegetation in fire models. Currently, the most advanced representations of fire behavior and biophysical fire effects are found in distinct classes of fine-scale models and do not capture variation in live fuel (i.e. living plant) properties. We demonstrate that plant water and carbon dynamics, which influence combustion and heat transfer into the plant and often dictate plant survival, provide the mechanistic linkage between fire behavior and effects. Our conceptual framework linking remotely sensed estimates of plant water and carbon to fine-scale models of fire behavior and effects could be a critical first step toward improving the fidelity of the coarse scale models that are now relied upon for global fire forecasting. This process-based approach will be essential to capturing the influence of physiological responses to drought and warming on live fuel conditions, strengthening the science needed to guide fire managers in an uncertain future

Bending the Carbon Curve: Fire Management for Carbon Resilience under Climate Change

Context: Forest landscapes are increasingly managed for fire resilience, particularly in the western US which has recently experienced drought and widespread, high-severity wildfires. Fuel reduction treatments have been effective where fires coincide with treated areas. Fuel treatments also have the potential to reduce drought-mortality if tree density is uncharacteristically high, and to increase long-term carbon storage by reducing high-severity fire probability. Objective: Assess whether fuel treatments reduce fire intensity and spread and increase carbon storage under climate change. Methods: We used a simulation modeling approach that couples a landscape model of forest disturbance and succession with an ecosystem model of carbon dynamics (Century), to quantify the interacting effects of climate change, fuel treatments and wildfire for carbon storage potential in a mixed-conifer forest in the western USA. Results: Our results suggest that fuel treatments have the potential to ‘bend the C curve’, maintaining carbon resilience despite climate change and climate-related changes to the fire regime. Simulated fuel treatments resulted in reduced fire spread and severity. There was partial compensation of C lost during fuel treatments with increased growth of residual stock due to greater available soil water, as well as a shift in species composition to more drought- and fire-tolerant Pinus jeffreyi at the expense of shade-tolerant, fire-susceptible Abies concolor. Conclusions: Forest resilience to global change can be achieved through management that reduces drought stress and supports the establishment and dominance of tree species that are more fire- and drought-resistant, however, achieving a net C gain from fuel treatments may take decades

Widespread severe wildfires under climate change lead to increased forest homogeneity in dry mixed-conifer forests

Climate warming in the western United States is causing changes to the wildfire regime in mixed-conifer forests. Rising temperatures, longer fire seasons, increased drought, as well as fire suppression and changes in land use, have led to greater and more severe wildfire activity, all contributing to altered forest composition over the past century. To understand future interactions among climate, wildfire, and vegetation in a fire-prone landscape in the southern Blue Mountains of central Oregon, we used a spatially explicit forest landscape model, LANDIS-II, to simulate forest and fire dynamics under current management practices and two projected climate scenarios. The results suggest that wildfires will become more frequent, more extensive, and more severe under projected climate than contemporary climate. Furthermore, projected climate change generated a 20% increase in the number of extreme fire years (years with at least 40,000 ha burned). This caused large shifts in tree species composition, characterized by a decline in the sub-alpine species (Abies lasiocarpa, Picea engelmannii, Pinus albicaulis) and increases in lowerelevation species (Pinus ponderosa, Abies grandis), resulting in forest homogenization across the elevational gradient. This modeling study suggests that climate-driven increases in fire activity and severity will make high-elevation species vulnerable to decline and will reduce landscape heterogeneity. These results underscore the need for forest managers to actively consider climate change, altered fire regimes, and projected declines in sub-alpine species in their long-term management plans

Effectiveness of Fuel Treatments for Mitigating Wildfire Risk and Sequestering Forest Carbon: A Case Study in the Lake Tahoe Basin

Fuel-reduction treatments are used extensively to reduce wildfire risk and restore forest diversity and function. In the near future, increasing regulation of carbon (C) emissions may force forest managers to balance the use of fuel treatments for reducing wildfire risk against an alternative goal of C sequestration. The objective of this study was to evaluate how long-term fuel treatments mitigate wildfires and affect forest C. For the Lake Tahoe Basin in the central Sierra Nevada, USA, fuel treatment efficiency was explored with a landscape-scale simulation model, LANDIS-II, using five fuel treatment scenarios and two (contemporary and potential future) fire regimes. Treatment scenarios included applying a combination of light (hand) and moderate (mechanical) forest thinning continuously through time and transitioning from these prescriptions to a more mid-seral thinning prescription, both on a 15 and 30 year rotation interval. In the last scenario, fuel treatments were isolated to around the lake shore (nearby urban settlement) to simulate a low investment alternative were future resources may be limited. Results indicated that the forest will remain a C sink regardless of treatment or fire regime simulated, due to the landscape legacy of historic logging. Achievement of a net C gain required decades with intensive treatment and depended on wildfire activity: Fuel treatments were more effective in a more active fire environment, where the interface between wildfires and treatment areas increased and caused net C gain earlier than as compared to our scenarios with less wildfire activity. Fuel treatments were most effective when continuously applied and strategically placed in high ignition areas. Treatment type and re-application interval were less influential at the landscape scale, but had notable effects on species dynamics within management units. Treatments created more diverse forest conditions by shifting dominance patterns to a more mixed conifer system, with a higher proportion of fire-tolerant species. We demonstrated that a small amount of wildfire on the landscape resulted in significant changes in the C pool, and that strategically placed fuel treatments substantially reduced wildfire risk, increased fire resiliency of the forest, and is beneficial for long-term C management. Implications for landscape management included consideration for prioritization of treatment areas and creating ideal re-entry schedules that meet logistic, safety, and conservation goals. In forests with a concentrated wildland urban interface, fuel treatments may be vital for ensuring human welfare and enhancing forest integrity in a fire-prone future