Wildfire-induced increases in photosynthesis in boreal forest ecosystems of North America

Observations of the annual cycle of atmospheric CO2 in high northern latitudes provide evidence for an increase in terrestrial metabolism in Arctic tundra and boreal forest ecosystems. However, the mechanisms driving these changes are not yet fully understood. One proposed hypothesis is that ecological change from disturbance, such as wildfire, could increase the magnitude and change the phase of net ecosystem exchange through shifts in plant community composition. Yet, little quantitative work has evaluated this potential mechanism at a regional scale. Here we investigate how fire disturbance influences landscape-level patterns of photosynthesis across western boreal North America. We use Alaska and Canadian large fire databases to identify the perimeters of wildfires, a Landsat-derived land cover time series to characterize plant functional types (PFTs), and solar-induced fluorescence (SIF) from the Orbiting Carbon Observatory-2 (OCO-2) as a proxy for photosynthesis. We analyze these datasets to characterize post-fire changes in plant succession and photosynthetic activity using a space-for-time approach. We find that increases in herbaceous and sparse vegetation, shrub, and deciduous broadleaf forest PFTs during mid-succession yield enhancements in SIF by 8-40% during June and July for 2- to 59-year stands relative to pre-fire controls. From the analysis of post-fire land cover changes within individual ecoregions and modeling, we identify two mechanisms by which fires contribute to long-term trends in SIF. First, increases in annual burning are shifting the stand age distribution, leading to increases in the abundance of shrubs and deciduous broadleaf forests that have considerably higher SIF during early- and mid-summer. Second, fire appears to facilitate a long-term shift from evergreen conifer to broadleaf deciduous forest in the Boreal Plain ecoregion. These findings suggest that increasing fire can contribute substantially to positive trends in seasonal CO2 exchange without a close coupling to long-term increases in carbon storage.

Qualitative value of information provides a transparent and repeatable method for identifying critical uncertainty

Conservation decisions are often made in the face of uncertainty because the urgency to act can preclude delaying management while uncertainty is resolved. In this context, adaptive management is attractive, allowing simultaneous management and learning. An adaptive program design requires the identification of critical uncertainties that impede the choice of management action. Quantitative evaluation of critical uncertainty, using the expected value of information, may require more resources than are available in the early stages of conservation planning. Here, we demonstrate the use of a qualitative index to the value of information (QVoI) to prioritize which sources of uncertainty to reduce regarding the use of prescribed fire to benefit Eastern Black Rails (Laterallus jamaicensis jamaicensis), Yellow Rails (Coterminous noveboracensis), and Mottled Ducks (Anas fulvigula; hereafter, focal species) in high marshes of the U.S. Gulf of Mexico. Prescribed fire has been used as a management tool in Gulf of Mexico high marshes throughout the last 30+ years; however, effects of periodic burning on the focal species and the optimal conditions for burning marshes to improve habitat remain unknown. We followed a structured decision-making framework to develop conceptual models, which we then used to identify sources of uncertainty and articulate alternative hypotheses about prescribed fire in high marshes. We used QVoI to evaluate the sources of uncertainty based on their Magnitude, Relevance for decision-making, and Reducibility. We found that hypotheses related to the optimal fire return interval and season were the highest priorities for study, whereas hypotheses related to predation rates and interactions among management techniques were lowest. These results suggest that learning about the optimal fire frequency and season to benefit the focal species might produce the greatest management benefit. In this case study, we demonstrate that QVoI can help managers decide where to apply limited resources to learn which specific actions will result in a higher likelihood of achieving the desired management objectives. Further, we summarize the strengths and limitations of QVoI and outline recommendations for its future use for prioritizing research to reduce uncertainty about system dynamics and the effects of management actions.

Resilience of temperate peatland vegetation communities to wildfire depends upon burn severity and pre-fire species composition

Peatland ecosystems are of global conservation and environmental importance storing globally significant amounts of ancient carbon, regulating regional temperatures and hydrological regimes, and supporting unique biodiversity. Livestock grazing, land-use change, drainage, nutrient and acid deposition, and wildfire threaten the composition and function of many peatlands including those in the uplands of the United Kingdom. Presently, little is known about either the short- or long-term effects of wildfires within these systems in the UK. Our study aimed to evaluate how plant communities respond to wildfires across a range of vegetation communities, soil types, and burn severities. We evaluated wildfire burn severity using the ground-based Composite Burn Index adapted for treeless peatlands. Using paired burned-unburned plots, we quantified differences in the abundance of plant families and functional groups, vegetation diversity, and community composition. Multivariate differences in composition between burned and unburned areas were used as an index of community resilience to fire. Plots in heathland communities with shallow organic soils burned at the highest severities and had the greatest reductions in plant diversity and richness. There were significant declines in plot-scale species richness and diversity with increasing burn severity. Graminoids were resilient to fire whilst Ericaceae tended to increase with higher severity. Bryophyte composition was substantially altered-pleurocarpous species declined and acrocarpous species increased with greater burn severity. Community resilience was related to ground layer burn severity with higher burn severity driving greater changes in communities. Wildfire effects on temperate peatlands are a function of fire weather and site environmental and ecological characteristics. Management policy should ensure that the risk of severe wildfires is mitigated to protect ecosystem function and biodiversity. This will require system-specific fire management prescriptions across the gradient of peatland soil and vegetation types.

Biogeographic variability in wildfire severity and post-fire vegetation recovery across the European forests via remote sensing-derived spectral metrics

Wildfires have large-scale and profound effects on forest ecosystems, and they force burned forest areas toward a wide range of post-fire successional trajectories from simple reduction of ecosystem functions to transitions to other stable non-forest states. Fire disturbances represent a key driver of changes in forest structure and composition due to post-fire succession processes, thus contributing to modify ecosystem resilience to subsequent disturbances. Here, we aimed to provide useful insights into wildfire severity and post-fire recovery processes at the European continental scale, contributing to improved description and interpretation of large-scale wildfire spatial patterns and their effects on forest ecosystems in the context of climate change. We analyzed fire severity and short-term post-fire vegetation recovery patterns across the European forests between 2004 and 2015 using Corine Land Cover Forest classes and bioregions, based on MODIS-derived spectral metrics of the relativized burn ratio (RBR), normalized difference vegetation index (NDVI) and relative recovery indicator (RRI). The RBR-based fire severity showed geographic differences and interannual variability in the Boreal bioregion compared to that in other biogeographic regions. The NBR-based RRI showed a slower post-fire vegetation recovery rate with respect to the NDVI, highlighting the differential sensitivities of the analyzed remote sensing-spectral metrics. Moreover, the RRI showed a significant decreasing trend during the observation period, suggesting a growing lag in post-fire vegetation recovery across European forests.

Global Surface Temperature: A New Insight

This paper belongs to our Special Issue “Application of Climate Data in Hydrologic Models” [...]

A Review of the Applications of Remote Sensing in Fire Ecology

Wildfire plays an important role in ecosystem dynamics, land management, and global processes. Understanding the dynamics associated with wildfire, such as risks, spatial distribution, and effects is important for developing a clear understanding of its ecological influences. Remote sensing technologies provide a means to study fire ecology at multiple scales using an efficient and quantitative method. This paper provides a broad review of the applications of remote sensing techniques in fire ecology. Remote sensing applications related to fire risk mapping, fuel mapping, active fire detection, burned area estimates, burn severity assessment, and post-fire vegetation recovery monitoring are discussed. Emphasis is given to the roles of multispectral sensors, lidar, and emerging UAS technologies in mapping, analyzing, and monitoring various environmental properties related to fire activity. Examples of current and past research are provided, and future research trends are discussed. In general, remote sensing technologies provide a low-cost, multi-temporal means for conducting local, regional, and global-scale fire ecology research, and current research is rapidly evolving with the introduction of new technologies and techniques which are increasing accuracy and efficiency. Future research is anticipated to continue to build upon emerging technologies, improve current methods, and integrate novel approaches to analysis and classification.

Burn Severity and Post-Fire Land Surface Albedo Relationship in Mediterranean Forest Ecosystems

Our study explores the relationship between land surface albedo (LSA) changes and burn severity, checking whether the LSA is an indicator of burn severity, in a large forest fire (117.75 km2, Spain). The LSA was obtained from Landsat data. In particular, we used an immediately-after-fire scene, a year-after-fire scene and a pre-fire one. The burn severity (three levels) was assessed in 111 field plots by using the Composite Burn Index (CBI). The potentiality of remotely sensed LSA as an indicator for the burn severity was tested by a one-way analysis of variance, correlation analysis and regression models. Specifically, we considered the total shortwave, visible, and near-infrared LSA. Immediately after the fire, we observed a decrease in the LSA for all burn severity levels (up to 0.631). A small increase in the LSA was found (up to 0.0292) a year after the fire. The maximum adjusted coefficient of determination (R2adj) of the linear regression model between the immediately post-fire LSA image and the CBI values was approximately 67%. Fisher’s least significance difference test showed that two burn severity levels could be discriminated by the immediately post-fire LSA image. Our results demonstrate that the magnitude of the changes in the LSA is related to the burn severity with a statistical significance, suggesting the potentiality of immediately-after-fire remotely sensed LSA for estimating the burn severity as an alternative to other satellite-based methods. However, the persistency of these changes in time should be evaluated in future research.

Temporal dynamics of albedo and climate in the sparse forests of Zagros

Land surface albedo is an important parameter affecting the climate locally and globally. A synthesis of current studies urgently calls for a better understanding of the impact of climate change on the surface albedo. The Middle East is expected to experience major climatic changes during the coming decades and has already undergone major losses in its vegetation cover. This study explores how climate change related disturbances, such as severe drought and fire events, influence albedo trends in the largest remaining forest area of the Middle East, the Zagros Mountains. We analyzed time series of albedo, Leaf Area Index (LAI), burn severity (dNBR), and the number of fire events all obtained from MODIS satellite images between 2000 and 2016, together with climatic data from 1950 to 2016. The Zagros area is continuously suffering from low precipitation, high temperatures, and evermore-frequent wildfire events. Our large-scale analysis revealed that albedo is linked to precipitation, number of fire events, dNBR, and LAI with the average correlation coefficients of -0.26, -0.50, 0.17, and -0.72, respectively. Using four study sites located in different parts of the Zagros area, we showed disturbances influence albedo differently. Drought condition resulted in a marginal increasing trend in albedo, whereas fire events resulted in a decreasing trend. This article is the first report linking climate change with albedo in Iran.

Measuring Landscape Albedo Using Unmanned Aerial Vehicles

Surface albedo is a critical parameter in surface energy balance, and albedo change is an important driver of changes in local climate. In this study, we developed a workflow for landscape albedo estimation using images acquired with a consumer-grade camera on board unmanned aerial vehicles (UAVs). Flight experiments were conducted at two sites in Connecticut, USA and the UAV-derived albedo was compared with the albedo obtained from a Landsat image acquired at about the same time as the UAV experiments. We find that the UAV estimate of the visibleband albedo of an urban playground (0.037 ± 0.063, mean ± standard deviation of pixel values) under clear sky conditions agrees reasonably well with the estimates based on the Landsat image (0.047 ± 0.012). However, because the cameras could only measure reflectance in three visible bands (blue, green, and red), the agreement is poor for shortwave albedo. We suggest that the deployment of a camera that is capable of detecting reflectance at a near-infrared waveband should improve the accuracy of the shortwave albedo estimation.

Regional atmospheric cooling and wetting effect of permafrost thaw-induced boreal forest loss

In the sporadic permafrost zone of North America, thaw-induced boreal forest loss is leading to permafrost-free wetland expansion. These land cover changes alter landscape-scale surface properties with potentially large, however, still unknown impacts on regional climates. In this study, we combine nested eddy covariance flux tower measurements with satellite remote sensing to characterize the impacts of boreal forest loss on albedo, eco-physiological and aerodynamic surface properties, and turbulent energy fluxes of a lowland boreal forest region in the Northwest Territories, Canada. Planetary boundary layer modelling is used to estimate the potential forest loss impact on regional air temperature and atmospheric moisture. We show that thaw-induced conversion of forests to wetlands increases albedo: and bulk surface conductance for water vapour and decreases aerodynamic surface temperature. At the same time, heat transfer efficiency is reduced. These shifts in land surface properties increase latent at the expense of sensible heat fluxes, thus, drastically reducing Bowen ratios. Due to the lower albedo of forests and their masking effect of highly reflective snow, available energy is lower in wetlands, especially in late winter. Modelling results demonstrate that a conversion of a present-day boreal forest-wetland to a hypothetical homogeneous wetland landscape could induce a near-surface cooling effect on regional air temperatures of up to 3-4 °C in late winter and 1-2 °C in summer. An atmospheric wetting effect in summer is indicated by a maximum increase in water vapour mixing ratios of 2 mmol mol^-1 . At the same time, maximum boundary layer heights are reduced by about a third of the original height. In fall, simulated air temperature and atmospheric moisture between the two scenarios do not differ. Therefore, permafrost thaw-induced boreal forest loss may modify regional precipitation patterns and slow down regional warming trends.

Early spring post-fire snow albedo dynamics in high latitude boreal forests using Landsat-8 OLI data

Taking advantage of the improved radiometric resolution of Landsat-8 OLI which, unlike previous Landsat sensors, does not saturate over snow, the progress of fire recovery progress at the landscape scale (< 100m) is examined. High quality Landsat-8 albedo retrievals can now capture the true reflective and layered character of snow cover over a full range of land surface conditions and vegetation densities. This new capability particularly improves the assessment of post-fire vegetation dynamics across low- to high- burn severity gradients in Arctic and boreal regions in the early spring, when the albedos during recovery show the greatest variation. We use 30 m resolution Landsat-8 surface reflectances with concurrent coarser resolution (500m) MODIS high quality full inversion surface Bidirectional Reflectance Distribution Functions (BRDF) products to produce higher resolution values of surface albedo. The high resolution full expression shortwave blue sky albedo product performs well with an overall RMSE of 0.0267 between tower and satellite measures under both snow-free and snow-covered conditions. While the importance of post-fire albedo recovery can be discerned from the MODIS albedo product at regional and global scales, our study addresses the particular importance of early spring post-fire albedo recovery at the landscape scale by considering the significant spatial heterogeneity of burn severity, and the impact of snow on the early spring albedo of various vegetation recovery types. We found that variations in early spring albedo within a single MODIS gridded pixel can be larger than 0.6. Since the frequency and severity of wildfires in Arctic and boreal systems is expected to increase in the coming decades, the dynamics of albedo in response to these rapid surface changes will increasingly impact the energy balance and contribute to other climate processes and physical feedback mechanisms. Surface radiation products derived from Landsat-8 data will thus play an important role in characterizing the carbon cycle and ecosystem processes of high latitude systems.

Toward a new radiative-transfer-based model for remote sensing of terrestrial surface albedo

This Letter formulates a simple yet accurate radiative-transfer-based theoretical model to characterize the fraction of radiation reflected by terrestrial surfaces. Emphasis is placed on the concept of inhomogeneous distribution of the diffuse sky radiation function (DSRF) and multiple interaction effects (MIE). Neglecting DSRF and MIE produces a -1.55% mean relative bias in albedo estimates. The presented model can elucidate the impact of DSRF on the surface volume scattering and geometry-optical scattering components, respectively, especially for slant illuminations with solar zenith angles (SZA) larger than 50°. Particularly striking in the comparisons between our model and ground-based observations is the achievement of the agreement level, indicating that our model can effectively resolve the longstanding issue in accurately estimating albedo at extremely large SZAs and is promising for land-atmosphere interactions studies.

Vegetation controls on northern high latitude snow-albedo feedback: observations and CMIP5 model simulations

The snow-masking effect of vegetation exerts strong control on albedo in northern high latitude ecosystems. Large-scale changes in the distribution and stature of vegetation in this region will thus have important feedbacks to climate. The snow-albedo feedback is controlled largely by the contrast between snow-covered and snow-free albedo (Δα), which influences predictions of future warming in coupled climate models, despite being poorly constrained at seasonal and century time scales. Here, we compare satellite observations and coupled climate model representations of albedo and tree cover for the boreal and Arctic region. Our analyses reveal consistent declines in albedo with increasing tree cover, occurring south of latitudinal tree line, that are poorly represented in coupled climate models. Observed relationships between albedo and tree cover differ substantially between snow-covered and snow-free periods, and among plant functional type. Tree cover in models varies widely but surprisingly does not correlate well with model albedo. Furthermore, our results demonstrate a relationship between tree cover and snow-albedo feedback that may be used to accurately constrain high latitude albedo feedbacks in coupled climate models under current and future vegetation distributions.