Exploring the effect of hydrological connectivity and soil burn severity on sediment yield after wildfire and mulching

2020 ◽  
Author(s):  
Cristina Fernández ◽  
José Ma Fernández‐Alonso ◽  
José A. Vega
Keyword(s):  
Sediment Yield ◽  
Burn Severity ◽  
Hydrological Connectivity ◽  
Soil Burn Severity

scholarly journals Evaluation of Composite Burn Index and Land Surface Temperature for Assessing Soil Burn Severity in Mediterranean Fire-Prone Pine Ecosystems

Forests ◽  
2018 ◽  
Vol 9 (8) ◽  
pp. 494 ◽  
Author(s):  
Elena Marcos ◽  
Víctor Fernández-García ◽  
Alfonso Fernández-Manso ◽  
Carmen Quintano ◽  
Luz Valbuena ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Surface Temperature ◽  
Soil Properties ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Burn Severity ◽  
Soil Burn Severity ◽  
Changes In Soil Properties

We analysed the relationship between burn severity indicators, from remote sensing and field observations, and soil properties after a wildfire in a fire-prone Mediterranean ecosystem. Our study area was a large wildfire in a Pinus pinaster forest. Burn severity from remote sensing was identified by studying immediate post-fire Land Surface Temperature (LST). We also evaluated burn severity in the field applying the Composite Burn Index (CBI) in a total of 84 plots (30 m diameter). In each plot we evaluated litter consumption, ash colour and char depth as visual indicators. We collected soil samples and pH, soil organic carbon, dry aggregate size distribution (MWD), aggregate stability and water repellency were analysed. A controlled heating of soil was also carried out in the laboratory, with soil from the control plots, to compare with the changes produced in soils affected by different severity levels in the field. Our results shown that changes in soil properties affected by wildfire were only observed in soil aggregation in the high severity situation. The laboratory-controlled heating showed that temperatures of about 300 °C result in a significant reduction in soil organic carbon and MWD. Furthermore, soil organic carbon showed a significant decrease when LST values increased. Char depth was the best visual indicator to show changes in soil properties (mainly physical properties) in large fires that occur in Mediterranean pine forests. We conclude that CBI and post-fire LST can be considered good indicators of soil burn severity since both indicate the impact of fire on soil properties.

scholarly journals Testing the Use of Forest Soil δ13C Shifts as a Post-Fire Index for Soil Burn Severity Estimation

Proceedings ◽  
2020 ◽  
Vol 30 (1) ◽  
pp. 49
Author(s):  
Fernandez ◽  
Cabaneiro
Keyword(s):  
Isotope Ratio Mass Spectrometry ◽  
Isotopic Signature ◽  
Forest Recovery ◽  
Burn Severity ◽  
Heating Process ◽  
Multilinear Regression ◽  
Solvent Fractionation ◽  
Soil C ◽  
Severity Estimation ◽  
Soil Burn Severity

Due to the increasing number and virulence of forest wildfires recently observed around the world, the establishment of a simple, accurate and reliable index that would correctly evaluate the fire effects on soil quality as a support for a suitable forest recovery management is becoming progressively more necessary. This objective is addressed here by using both δ13C isotope ratio mass spectrometry and traditional solvent fractionation methods (widely used to assess soil biogenic components or humus fractions) to quantify the temperature-induced changes in soil chemical and isotopic composition. Soil samples from the upper 5 cm layer of two Cambisols developed over granite under pine forest in the NW of Spain were heated in an oven under controlled conditions to attain moderate or intense soil burn severity levels by using two different temperatures (220 °C or 350 °C). Biochemical changes induced by the heating process appreciably differed according to the intensity of the temperature applied. Multilinear regression modelling not only showed a significant relationship between soil C isotopic signature shifts (Δsoil δ13C) with temperature increases but also revealed other key outcomes: i.e., >96 or >81% of its total variance can be predicted by changes in lignin or non-humified organic matter, respectively. Indeed, Δsoil δ13C explained by itself ≈60% of thermal variance, pointing to the aptness of using 13C shifts as a valid index for soil burn severity estimation in wildfires.

Challenges of assessing fire and burn severity using field measures, remote sensing and modelling

2014 ◽  
Vol 23 (8) ◽  
pp. 1045 ◽  
Author(s):  
Penelope Morgan ◽  
Robert E. Keane ◽  
Gregory K. Dillon ◽  
Theresa B. Jain ◽  
Andrew T. Hudak ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Simulation Models ◽  
Severity Index ◽  
Fire Effects ◽  
Burn Severity ◽  
Ecological Change ◽  
Continuous Variables ◽  
Field Methods ◽  
Soil Burn Severity ◽  
Effective Assessment

Comprehensive assessment of ecological change after fires have burned forests and rangelands is important if we are to understand, predict and measure fire effects. We highlight the challenges in effective assessment of fire and burn severity in the field and using both remote sensing and simulation models. We draw on diverse recent research for guidance on assessing fire effects on vegetation and soil using field methods, remote sensing and models. We suggest that instead of collapsing many diverse, complex and interacting fire effects into a single severity index, the effects of fire should be directly measured and then integrated into severity index keys specifically designed for objective severity assessment. Using soil burn severity measures as examples, we highlight best practices for selecting imagery, designing an index, determining timing and deciding what to measure, emphasising continuous variables measureable in the field and from remote sensing. We also urge the development of a severity field assessment database and research to further our understanding of causal mechanisms linking fire and burn severity to conditions before and during fires to support improved models linking fire behaviour and severity and for forecasting effects of future fires.

BAER Soil Burn Severity Maps Do Not Measure Fire Effects to Vegetation: A Comment on Odion and Hanson (2006)

Ecosystems ◽  
2007 ◽  
Vol 11 (1) ◽  
pp. 1-11 ◽  
Author(s):  
Hugh D. Safford ◽  
Jay Miller ◽  
David Schmidt ◽  
Brent Roath ◽  
Annette Parsons
Keyword(s):  
Fire Effects ◽  
Burn Severity ◽  
Soil Burn Severity

scholarly journals Mapping Soil Burn Severity at Very High Spatial Resolution from Unmanned Aerial Vehicles

Forests ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 179
Author(s):  
David Beltrán-Marcos ◽  
Susana Suárez-Seoane ◽  
José Manuel Fernández-Guisuraga ◽  
Víctor Fernández-García ◽  
Rayo Pinto ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Burn Severity ◽  
Spectral Indices ◽  
Aerial Vehicles ◽  
Soil Burn Severity ◽  
Debris Cover ◽  
Very High Spatial Resolution ◽  
Very High

The evaluation of the effect of burn severity on forest soils is essential to determine the impact of wildfires on a range of key ecological processes, such as nutrient cycling and vegetation recovery. The main objective of this study was to assess the potentiality of different spectral products derived from RGB and multispectral imagery collected by unmanned aerial vehicles (UAVs) at very high spatial resolution for discriminating spatial variations in soil burn severity after a heterogeneous wildfire. In the case study, we chose a mixed-severity fire that occurred in the northwest (NW) of the Iberian Peninsula (Spain) in 2019 that affected 82.74 ha covered by three different types of forests, each dominated by Pinus pinaster, Pinus sylvestris, and Quercus pyrenaica. We evaluated soil burn severity in the field 1 month after the fire using the Composite Burn Soil Index (CBSI), as well as a pool of five individual indicators (ash depth, ash cover, fine debris cover, coarse debris cover, and unstructured soil depth) of easy interpretation. Simultaneously, we operated an unmanned aerial vehicle to obtain RGB and multispectral postfire images, allowing for deriving six spectral indices. Then, we explored the relationship between spectral indices and field soil burn severity metrics by means of univariate proportional odds regression models. These models were used to predict CBSI categories, and classifications were validated through confusion matrices. Results indicated that multispectral indices outperformed RGB indices when assessing soil burn severity, being more strongly related to CBSI than to individual indicators. The Normalized Difference Water Index (NDWI) was the best-performing spectral index for modelling CBSI (R2cv = 0.69), showing the best ability to predict CBSI categories (overall accuracy = 0.83). Among the individual indicators of soil burn severity, ash depth was the one that achieved the best results, specifically when it was modelled from NDWI (R2cv = 0.53). This work provides a useful background to design quick and accurate assessments of soil burn severity to be implemented immediately after the fire, which is a key factor to identify priority areas for emergency actions after forest fires.

Rapid-response tools and datasets for post-fire remediation: linking remote sensing and process-based hydrological models

2016 ◽  
Vol 25 (10) ◽  
pp. 1061 ◽  
Author(s):  
M. E. Miller ◽  
W. J. Elliot ◽  
M. Billmire ◽  
P. R. Robichaud ◽  
K. A. Endsley
Keyword(s):  
Remote Sensing ◽  
Soil Properties ◽  
Remote Sensing Data ◽  
Burn Severity ◽  
Spatially Explicit ◽  
Vegetative Cover ◽  
Sediment Delivery ◽  
Soil Burn Severity ◽  
Set Up ◽  
Induced Changes

Post-wildfire flooding and erosion can threaten lives, property and natural resources. Increased peak flows and sediment delivery due to the loss of surface vegetation cover and fire-induced changes in soil properties are of great concern to public safety. Burn severity maps derived from remote sensing data reflect fire-induced changes in vegetative cover and soil properties. Slope, soils, land cover and climate are also important factors that require consideration. Many modelling tools and datasets have been developed to assist remediation teams, but process-based and spatially explicit models are currently underutilised compared with simpler, lumped models because they are difficult to set up and require properly formatted spatial inputs. To facilitate the use of models in conjunction with remote sensing observations, we developed an online spatial database that rapidly generates properly formatted modelling datasets modified by user-supplied soil burn severity maps. Although assembling spatial model inputs can be both challenging and time-consuming, the methods we developed to rapidly update these inputs in response to a natural disaster are both simple and repeatable. Automating the creation of model inputs facilitates the wider use of more accurate, process-based models for spatially explicit predictions of post-fire erosion and runoff.

Testing the ability of visual indicators of soil burn severity to reflect changes in soil chemical and microbial properties in pine forests and shrubland

2012 ◽  
Vol 369 (1-2) ◽  
pp. 73-91 ◽  
Author(s):  
José A. Vega ◽  
Teresa Fontúrbel ◽  
Agustín Merino ◽  
Cristina Fernández ◽  
Andrea Ferreiro ◽  
...  
Keyword(s):  
Pine Forests ◽  
Burn Severity ◽  
Microbial Properties ◽  
Soil Burn Severity

Burn Severity Effects on Sediment and Nutrient Exports from Southeastern Forests Using Simulated Rainfall

2020 ◽  
Vol 66 (6) ◽  
pp. 678-686 ◽  
Author(s):  
Kipling Klimas ◽  
Patrick Hiesl ◽  
Donald Hagan ◽  
Dara Park
Keyword(s):  
Sediment Yield ◽  
Suspended Solids ◽  
Total Suspended Solids ◽  
Burn Severity ◽  
Nutrient Concentrations ◽  
Simulated Rainfall ◽  
Forest Types ◽  
Important Indicator ◽  
Nutrient Response ◽  
High Severity

Abstract Burn severity, commonly assessed as the amount of fuel consumed during fire, is an indicator of postfire sediment yield and erosion. This study examined the effect of burn severity on sediment and nutrient response in three different fire-adapted forest types of the Southeast. Soil and litter samples were experimentally burned to achieve increasing levels of fuel consumption. Simulated rainfall was applied to burned litter samples collected from pine, hardwood, and mixed hardwood-pine forests in the Clemson Experimental Forest. Runoff and leachate samples were collected and analyzed for sediment yield (kilograms per hectare) and total suspended solids (grams per liter); both runoff and leachate samples were analyzed for ammonium (NH4–), nitrate (NO3–), and orthophosphate (PO43–). Sediment yield and total suspended solids increased at only the highest burn severity treatment in all three forest types, with pine litter samples yielding significantly greater sediment in surface runoff than both mixed and hardwood samples. Burn treatment did not readily affect soluble nutrient concentrations in either runoff or leachate, but the data suggest that high-severity burning increases the availability of PO43– bound to sediment. This study suggests that high-severity burn patches function as sediment sources, but overall sediment and nutrient response to burning was minimal. Study Implications This study suggests that low-to-moderate burn severity, in terms of litter removal, is not an important indicator of sediment and nutrient exports from southeastern forests; precipitation in the immediate aftermath of fire (<48 hours) is not an effective transport mechanism for biologically available macronutrients; and that even at the highest burn severity treatment, sediment yield was relatively low.

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