Post-fire Vegetation Recovery Research Articles

Divergent biophysical responses of western United States forests to wildfire driven by eco-climatic gradients

Abstract. Understanding vegetation recovery after fire is critical for predicting vegetation-mediated ecological dynamics in future climates. However, information characterizing vegetation recovery patterns after fire and their determinants over large geographical extents is limited. This study uses Moderate Resolution Imaging Spectroradiometer (MODIS) leaf area index (LAI) and albedo to characterize patterns of post-fire biophysical dynamics across the western United States (US) and further examines the influence of topo-climatic variables on the recovery of LAI and albedo at two different time horizons, 10 and 20 years post-fire, using a random forest model. Recovery patterns were derived for all wildfires that occurred between 1986 and 2017 across seven forest types and 21 level III ecoregions of the western US. We found differences in the characteristic trajectories of post-fire vegetation recovery across forest types and eco-climatic settings. In some forest types, LAI had recovered to only 60 %–70 % of the pre-fire levels by 25 years after the fire, while it recovered to 120 %–150 % of the pre-fire levels in other forest types, with higher absolute post-fire changes observed in forest types and ecoregions that had a higher initial pre-fire LAI. Our random forest results showed very little influence of fire severity on the recovery of both summer LAI and albedo at both post-fire time horizons. Post-fire vegetation recovery was most strongly controlled by elevation, with faster rates of recovery at lower elevations. Similarly, annual precipitation and average summer temperature had significant impacts on the post-fire recovery of vegetation. Full recovery was seldom observed when annual precipitation was less than 500 mm and average summer temperature was above the optimal range, i.e., 15–20 °C. Climate influences, particularly annual precipitation, were a major driver of post-fire summer albedo change through its impact on ecological succession. This study provides quantitative measures of primary controls that could be used to improve the modeling of ecosystem dynamics post-fire.

Climate limits vegetation green-up more than slope, soil erodibility, and immediate precipitation following high-severity wildfire

BackgroundIn the southwestern United States, post-fire vegetation recovery is increasingly variable in forest burned at high severity. Many factors, including temperature, drought, and erosion, can reduce post-fire vegetation recovery rates. Here, we examined how year-of-fire precipitation variability, topography, and soils influenced post-fire vegetation recovery in the southwestern United States as measured by greenness to determine whether erosion-related factors would have persistent effects in the longer post-fire period. We modeled relationships between post-fire vegetation and these predictors using random forest and examined changes in post-fire normalized burn ratio across fires in Arizona and New Mexico. We incorporated growing season climate to determine if year-of-fire effects were persistent during the subsequent 5 years or if temperature, water deficit, and precipitation in the years following fire were more influential for vegetation greenness. We expected that post-fire factors that drive erosion would reduce greenness; however, these effects would explain less variability in post-fire greenness than growing season climate.ResultsWe found reductions in post-fire greenness in areas burned at high severity when heavy and intense precipitation fell on more erodible soils immediately post-fire. In highly erodible scenarios, when accounting for growing season climate, coefficient of variation for year-of-fire precipitation, total precipitation, and soil erodibility decreased greenness in the fifth year. However, more of the variation in greenness was explained by variability of growing season vapor pressure deficit and growing season precipitation.ConclusionsOur results suggest that while the factors that contribute to post-fire erosion and its effects on vegetation recovery are important, at a regional scale, the majority of the variability in post-fire greenness in high-severity burned areas in southwestern forests is due to climatic drivers such as growing season precipitation and vapor pressure deficit. Given the increasing scale of area burned at high severity and the potential for more post-fire erosion, quantifying how these factors alter ecosystem development is central to understanding how different ecosystem types will be distributed across these landscapes with additional climate change.

Stratified burn severity assessment by integrating spaceborne spectral and waveform attributes in Great Xing'an Mountain

Burn severity assessment is critical for understanding the pattern of post-fire vegetation recovery and ecosystem resilience. Previous studies proposed various field criteria (e.g., Composite Burn Index (CBI)) to quantify burn severity from strata level to total site level, yet suffering from surveyors' subjective interpretation across site conditions. High-resolution passive remote sensing allows for more objective assessment based on the strong relation between fire damages and spectral features. Importantly, burn severity generally characterizes differences between forest overstory and understory layers due to their discrepancies in vegetation structures and environmental conditions. Spatially explicit mapping of strata-level burn severity is vital for post-fire forest management and ecological function evaluation. Until now, almost no available spaceborne remote sensing method can concurrently assess overstory and understory burn severity over heterogeneous forests. In this study, we proposed a Hybrid Composite Burn Index (HCBI) that comprehensively indicates the fire-induced spectral and structural changes along the vertical profile by integrating spectral and waveform attributes from both active and passive remote sensing data. Firstly, we introduced two remote sensing-based rating factors namely relative spectral change (RSC) and relative waveform change (RWC), and established HCBI through weighting and scoring the rating factors. Subsequently, we evaluated the effectiveness and generality of overstory, understory, and total site HCBI based on various pairs of simulated remote sensing data of pre-fire and post-fire forest scenes. Thirdly, we derived the spatially discontinuous maps of overstory, understory, and total site HCBI of the Xiushan fire site in Great Xing'an Mountain using WorldView-2 (WV-2) multispectral imagery and Global Ecosystem Dynamics Investigation (GEDI) full-waveform LiDAR data. Finally, we produced wall-to-wall HCBI maps using multiple predictive variables from pre-fire and post-fire Sentinel-2 MultiSpectral Instrument (MSI) images with a Random Forest (RF) algorithm. The predicted overstory, understory, and total site HCBI were validated by field-surveyed CBI. The assessment results based on simulation data showed HCBI was sensitive to the fire damage regardless of burn severity levels and vegetation cover levels (R2 of larger than 0.97 and RMSE of <0.15). The prediction results based on RF models achieved reliable HCBI of the total site, overstory, and understory levels (R2 of around 0.85 and RMSE of around 0.30). We found the wall-to-wall maps of HCBI captured the subtle horizontal and vertical variation even in the case of understory burn alone. We concluded that the newly proposed HCBI can advance the remote sensing-based assessment of stratified burn severity, offering opportunities for making fine-scale forest management decisions.

Differential Post-Fire Vegetation Recovery of Boreal Plains Bogs and Margins

Differential Post-Fire Vegetation Recovery of Boreal Plains Bogs and Margins

Plant-plant interactions influence post-fire recovery depending on fire history and nurse growth form

BackgroundsPlant-plant interactions are among the most important factors affecting the natural recovery of vegetation. While the impacts of nurse plants on species composition and biodiversity are well documented, the effects of different nurse’s growth forms on all biodiversity components including taxonomic, functional, and phylogenetic diversity have been less studied and compared, especially for their effects on different times after fire disturbance. This research was focused on comparing the effects of a perennial grass (Elymus hispidens), a perennial herb (Phlomis cancellata), and a high shrub species (Lonicera nummulariifolia) on species composition and the biodiversity components, and how these impacts change across five sites with short-term (1 and 4 years sites), long-term (10 and 20 years sites) times since last fire and a control site where no fire was known in recorded history in semi-arid shrublands of Fereizi Chenaran located in Northeast of Iran. The changes of species composition and taxonomic, functional, and phylogenetic diversity were calculated with respect to the presence/absence of nurse’s growth forms, fire history, and their interactions.ResultsNurse shrubs affected species composition and all biodiversity components, whereas all indices were reduced when considering Elymus grass as nurse plant. On the other hand, the herb Phlomis enhanced species composition and taxonomic diversity, while it had a negative effect on functional and phylogenetic diversity. Such specific effects of nurse types were mostly observed under long timescales (i.e., 10- and 20-year sites). Interestingly, the relative importance of nurse types and time since the last fire largely explained the variation of species composition and biodiversity components, with larger effects of nurse types on all biodiversity components. However, we found a significant contribution of fire explaining variation of species composition and phylogenetic diversity.ConclusionsThese results indicated nurse plants can affect the post-fire recovery of vegetation by providing specific mechanisms controlling beneficiary relatedness depending on their growth forms and time scales since the last fire. Therefore, these findings suggest perennial plants in the form of nurse species as a useful factor to develop techniques of active restoration in burned ecosystems.

Long-term evaluation of soil functionality in Mediterranean forests after a wildfire and post-fire hillslope stabilisation

The effects of hillslope stabilisation techniques on soil properties and vegetation cover of Mediterranean forests affected by wildfires have been deeply explored in the short term, while the long-term evaluations are scarce. Following previous investigations carried out in a pine forest of Castilla-La Mancha (Spain) burned by a severe wildfire in 2012 and treated with log erosion barriers (LEBs) or contour felled log debris (CFD) as post-fire management actions, this study evaluates the changes in soil physico-chemical and biological properties, and vegetation cover eleven years after the fire and structure construction in unburned, burned and untreated (with north or south aspect), and burned and treated soils (with CFDs or LEBs). The results have shown that none of the physico-chemical and biological properties of soil as well as the ground cover significantly differs between sites treated with CFDs and LEBs. The latter structures appear to be more effective in storing organic matter and water in the soil, which is important for post-fire vegetation recovery. The aforementioned effectiveness of post-fire treatments in limiting the changes in soil and vegetation due to wildfire was particularly evident in the burned and untreated sites exposed to the south, which should be prioritised for treatment, since these areas show long-term reductions in soil water content and availability. This prioritisation helps to support a quicker restoration of vegetation cover, which may find water shortage as a limiting factor compared to sites with north aspect. Finally, since, in such a long term, the changes in several soil properties (e.g., most of the enzymatic activities and basal respiration) between unburned, and burned and treated sites disappeared, and vegetation cover was almost fully restored up to the unburned level, it can be confirmed that the analysed hillslope stabilisation techniques were successful in recovering the pre-fire conditions of soil and vegetation conditions that are typical of unburned sites.

Post-fire recovery of Puya raimondii, vegetation and birds in the puna of Huascarán National Park, Perú

Post-fire recovery of Puya raimondii, vegetation and birds in the puna of Huascarán National Park, Perú

Fire-modulated fluctuations in nutrient availability stimulate biome-scale floristic turnover in time, and elevated species richness, in low-nutrient fynbos heathland.

In many systems, postfire vegetation recovery is characterized by temporal changes in plant species composition and richness. We attribute this to changes in resource availability with time since fire, with the magnitude of species turnover determined by the degree of resource limitation. Here, we test the hypothesis that postfire species turnover in South African fynbos heathland is powered by fire-modulated changes in nutrient availability, with the magnitude of turnover in nutrient-constrained fynbos being greater than in fertile renosterveld shrubland. We also test the hypothesis that floristic overlaps between fynbos and renosterveld are attributable to nutritional augmentation of fynbos soils immediately after fire. We use vegetation survey data from two sites on the Cape Peninsula to compare changes in species richness and composition with time since fire. Fynbos communities display a clear decline in species richness with time since fire, whereas no such decline is apparent in renosterveld. In fynbos, declining species richness is associated with declines in the richness of plant families having high foliar concentrations of nitrogen, phosphorus and potassium and possessing attributes that are nutritionally costly. In contrast, families that dominate late-succession fynbos possess adaptations for the acquisition and retention of sparse nutrients. At the family level, recently burnt fynbos is compositionally more similar to renosterveld than is mature fynbos. Our data suggest that nutritionally driven species turnover contributes significantly to fynbos community richness. We propose that the extremely low baseline fertility of fynbos soils serves to lengthen the nutritional resource axis along which species can differentiate and coexist, thereby providing the opportunity for low-nutrient extremophiles to coexist spatially with species adapted to more fertile soil. This mechanism has the potential to operate in any resource-constrained system in which episodic disturbance affects resource availability.

Post-fire recovery of vegetation in the Chornobyl Radiation and Ecological Biosphere Reserve

ABSTRACT Fires significantly affect the structure and diversity of vegetation. Natural recovery of vegetation after fires in the Chornobyl Exclusion Zone is of special interest because of its status as a nuclear disaster area. This is the first assessment of the potential for natural regrowth of forest and post-fire succession after the catastrophic fires of 2020 that scorched 62 000 ha of forest across the territory. Most of these areas (>80%) have high potential for natural regeneration but, in the first instance, forest species are commonly replaced by wasteland weeds, some of them invasive; 10 alien plant species were identified in the studied plots. Megafires facilitate vegetation shifts and opportunities for invasive species, especially in the early stages of succession.

Short-term recovery of post-fire vegetation is primarily limited by drought in Mediterranean forest ecosystems

BackgroundClimate change is altering the fire regime and compromising the post-fire recovery of vegetation worldwide. To understand the factors influencing post-fire vegetation cover restoration, we calculated the recovery of vegetation in 200,000 hectares of western Mediterranean forest burned by 268 wildfires over a 27-year period (1988–2015). We used time series of the Tasseled Cap Transformation Brightness (TCTB) spectral transformation over Landsat imagery to calculate vegetation recovery. Then, we quantified the importance of the main drivers of post-fire vegetation recovery (climate, fire severity, and topography) along an aridity gradient (semi-arid, sub-humid, and humid) using Random Forest models.ResultsIn most models (99.7%), drought duration was the most important factor, negatively affecting post-fire recovery especially in the extremes of the aridity gradient. Fire severity was the second most important factor for vegetation cover recovery, with its effect varying along the aridity gradient: there was a positive relationship between fire severity and recovery in sub-humid and humid areas, while semi-arid areas showed the opposite pattern. Topographic variables were the least important driver and had a marginal effect on post-fire recovery. Additionally, semi-arid areas exhibited a low mean recovery rate, indicating limitations in the short-term recovery after a fire.ConclusionsOur study highlights the key role that drought duration plays in the recovery of vegetation after wildfires in the Mediterranean basin and, particularly, in forests located in climatically extreme areas. The results suggest that the predicted increase in drought duration coupled with a higher frequency and intensity of large fires may modify the structure and composition of Mediterranean forest ecosystems. Our analysis provides relevant information to evaluate and design adaptive management strategies in post-fire recovery hotspots of Mediterranean forest ecosystems.

Monitoring immediate post-fire vegetation dynamics of tropical mountain grasslands using phenocameras

The growing incidence of uncontrolled wildfires all over the globe has called for urgent close monitoring of fire events, awareness, prevention, and management approaches. Phenocameras, ground sensors for monitoring plant phenology by taking sequential RGB digital images, can be an accessible and accurate tool for identifying, monitoring, and analyzing fire events and vegetation recovery. Here, we evaluated the application of an RGB camera system as a methodological approach to monitor and assess the post-fire recovery of a tropical mountain grasslands, the Brazilian campo rupestre. Using camera-derived vegetation indices, we investigated the immediate post-fire regrowth, and short-term post-fire leafing among four vegetation types: wet grassland, peatbog, stony grassland, and rocky outcrop. We recorded significant variations in the post-fire recovery among the grassy vegetation types. The results indicated that fire represents an important driver of leafing dynamics by shortening the length of post-fire growing seasons. The phenological metric of growing season length (GSL) indicated a full post-fire ecosystem recovery in the third year after the fire. The green-up index represented well the dynamics of post-fire vegetation regrowth and recovery across the landscape. Phenocameras rapidly detected fire occurrence and post-fire vegetation responses across vegetation types, demonstrating their significant application in the fire ecology of grassy ecosystems. The accessible, low-cost, and easy-to-setup camera system allows the application of near-remote phenology as a monitoring system and an indicator of vegetation recovery, which may improve restoration and management plans, promoting the conservation of the highly diverse campo rupestre grassland ecosystems.

Higher burn severity stimulates postfire vegetation and carbon recovery in California

As the climate continues to warm, the severity of wildfires is increasing. However, the potential impact of higher burn severity on ecosystem resilience and regional carbon balance is still not clear. There are ongoing debates regarding whether increased burn severity stimulates or delays postfire vegetation and carbon recovery. In this study, we utilized remote sensing data to analyze burn severity and vegetation observations, as well as model simulations to assess wildfire carbon emissions and ecosystem carbon fluxes. Our focus was on examining the dynamics of vegetation and carbon flux following wildfires spanning up to 16 years in California, a region that has experienced significant intensification in burn severity over the past two decades. Our findings revealed that more severe burns resulted in greater vegetation damage and carbon releases. However, they also facilitated faster postfire vegetation and carbon recovery. In comparison to the average burn severity, the most severe burns caused an additional 62–128 % loss of vegetation, 21–80 % higher instant wildfire carbon emissions, and 45–110 % more postfire carbon sources. Nonetheless, high-severity burns exhibited accelerated postfire recoveries in both vegetation growth and ecosystem carbon sink. Carbon sinks, which persisted for up to 15 years after high-severity burns, partially offset a significant proportion of the extra postfire carbon sources, ranging from 84 to 107 % (excluding instant emissions). However, this offset effect was insufficient to fully compensate for the combined impact of postfire carbon sources and instant wildfire carbon emissions. Consequently, on the decadal time scale relevant to regional climate policies, the increasing severity of fires poses a threat to the objective of maintaining California's natural and working lands as a net carbon sink. Moreover, it exacerbates climate warming by enhancing carbon releases from ecosystems.

Elucidating factors driving post-fire vegetation recovery in the Mediterranean forests using Landsat spectral metrics

Wildfires represent one of the primary disturbance agents in the Mediterranean, significantly affecting the ecological integrity of forests. Therefore, understanding the spatial patterns of post-fire vegetation recovery is crucial to improving forest restoration planning and assessing the regeneration capacity of different forest stands that have been impacted by wildfires. In this study, we analysed post-fire vegetation recovery rates within the context of fire severity, pre-fire vegetation, and post-fire climate conditions, for different Mediterranean forest classes, namely, Mediterranean pine, holm, deciduous oak forests, sclerophyllous vegetation, and thermophilous shrublands. Basilicata, in Italy, was chosen as a study area, as it represents a wide range of forests.The Relative Recovery Indicator (RRI) was derived from Normalized Burn Ratio (NBR) patterns extracted from 30-meter Landsat time series for different wildfires that occurred during the 2004–2016 within Google Earth Engine (GEE) environment. A Linear Mixed Model (LMM) was used to test the effect of the different variables on the RRI. Results showed a general decrease in recovery rate within five-years post-fire for each forest cover class, which is mainly related to pre- and post-fire conditions. Pre-fire vegetation conditions significantly influenced post-fire vegetation recovery, especially in sclerophyllous and deciduous oak forests. Post-fire climate conditions (e.g., temperature) were also important predictors of vegetation recovery explaining the variation in post-fire RRI patterns. The proposed method could provide new insights into the restoration and management of forest ecosystems in the Mediterranean.

Remote sensing delineation of wildfire spatial extents and post-fire recovery along a semi-arid climate gradient

Understanding the wildfire extent and post-fire vegetation recovery is critical for fire and forest management. Remote sensing imagery is widely used in wildfire detection because it provides continuous and large-scale surface monitoring capability. In this study, we apply and evaluate the performance of the LandTrendr algorithm in wildfire detection across a semi-arid climate region with a marked precipitation gradient. The aims are to compare the performance of four spectral indices for the burned areas and post-fire recovery detection for different climate conditions and investigate the relationship between suitable model parameters and climate conditions. The results show that NDVI outperforms other indices, including NBR, in burned area detection for drier areas (annual precipitation <400 mm). Disturbance signal-to-noise ratio can serve as an indicator for suitable index selection for semi-arid areas. Although the performance in the detection of burned pixels varies among different indices, they are all suitable for delineating post-fire recovery except for the wet site (annual precipitation of 575 mm) where NBR displays the best performance. Parameter optimization results along the climate gradient show that climate conditions have a significant impact on suitable parameter selection. These findings provide guidance on vegetation wildfire detection in arid and semi-arid climates to support wildfire risk and forestry management.

The influence of postfire recovery and environmental conditions on boreal vegetation

AbstractClimate change is increasing the frequency and extent of fires in the boreal biome of North America. These changes can alter the recovery of both canopy and understory vegetation. There is uncertainty about plant and lichen recovery patterns following fire, and how they are mediated by environmental conditions. Here, we aim to address these knowledge gaps by studying patterns of postfire vegetation recovery at the community and individual species level over the first 100+ years following fire. Data from vegetation surveys collected from 581 plots in the Northwest Territories, Canada, ranging from 1 to 275 years postfire, were used to assess the influence of time after fire and local environmental conditions on plant community composition and to model trends in the relative abundance of several common plant and lichen species. Time after fire significantly influenced vegetation community composition and interacted with local environmental conditions, particularly soil moisture. Soil moisture individually (in the absence of interactions) was the most commonly significant variable in plant and lichen recovery models. Patterns of postfire recovery varied greatly among species. Our results provide novel information on plant community recovery after fire and highlight the importance of soil moisture to local vegetation patterns. They will aid northern communities and land managers to anticipate the impacts of increased fire activity on both local vegetation and the wildlife that relies on it.

Vegetation recovery drivers at short-term after fire are plant community-dependent in mediterranean burned landscapes

Large, severe wildfires can cause unpredictable changes in Mediterranean plant communities that undermine ecosystem resilience. Understanding the geophysical drivers shaping vegetation dynamics after fire is vital to provide integrated knowledge into plant community recovery feedbacks in the context of global change. We investigated the role of fire severity and a comprehensive set of geophysical drivers in the post-fire vegetation recovery of Mediterranean landscapes. We used physical-based remote sensing techniques to estimate vegetation recovery and examined whether this recovery is plant-community dependent in the short-term (one year) after the fire. The fractional vegetation cover (FCOVER) recovery was selected as a resilience indicator for Pinus sylvestris L. (Scots pine) forests, Quercus ilex L. (holm oak) woodlands, shrublands dominated by Cytisus oromediterraneus Rivas Mart. et al. (black broom) and grasslands. To obtain the pre- and post-fire FCOVER, we used the Gaussian processes regression algorithm trained with the PROSAIL-D radiative transfer model. The algorithm was parameterized to account for the variability of biophysical conditions in the plant communities considered and was applied to the Sentinel-2 multispectral imagery. Validation of remotely-sensed FCOVER with field data in burned and control plots was successful (R2 = 0.84 and RMSE = 10.83%), without significant under or overestimation. We selected 31 variables pertaining to fire severity, climate, post-fire soil moisture, pre-fire soil condition, and landscape configuration as putative predictors of FCOVER recovery percentage (FCOVER%rec), calculated as the ratio of post-fire to pre-fire FCOVER. Random Forest regression (RFR) was used to disentangle the influences of fire severity and geophysical drivers on community-specific FCOVER%rec. Fire severity and post-fire surface soil moisture variables were relevant predictors in RFR models in all plant communities. However, their importance was largely community-dependent. In grasslands, surface soil moisture in the early summer season one year after fire was the major variable explaining variability in FCOVER%rec. In holm oak woodlands, the contribution of fire severity and surface soil moisture was balanced. Conversely, fire severity largely outweighed other variables in driving FCOVER%rec in black broom shrublands and Scots pine forests. Pre-fire climate, soil condition and landscape configuration variables were not meaningful predictors in general. Our findings offer novel insights into the processes that underlie resilience in fire-prone plant communities located in the western Mediterranean Basin. This establishes a baseline to help prioritize adaptive management strategies for the most vulnerable areas in the region.

Differentiating effects of salvage logging and recovery patterns on post-fire boreal forests in Northeast China using a modified forest disturbance index

ABSTRACT Forests are resilient to a range of disturbances, but combinations of severe natural and anthropogenic disturbances (e.g. wildfire and logging) may inhibit forest recovery and lead to forest degradation. Recent studies have explored long-term forest-disturbance detection and forest-recovery dynamics by using free and open-access remote-sensing images. However, mapping consecutive multiple disturbance agents is challenging using existing automated change-detection algorithms because the reduced canopy reflectance and the smoothing of consecutive disturbance signals mean that the initial disturbance cannot be spectrally separated from the second disturbance. Furthermore, uncertainty remains about post-disturbance vegetation dynamics and the effects of forest recovery under the interaction of burn severity, biological-legacy management, and active forest restoration (i.e. artificial regeneration and assisted natural regeneration). This contributes to biases in long-term forest-recovery monitoring, which are not conducive to the guidance of post-fire vegetation recovery. Here, we propose a modified disturbance index to separate the spectral characteristics of fire and forest logging using normalized tasseled-cap components (brightness and wetness) and detect the spatiotemporal distribution of post-fire logging by means of an index threshold and image differencing. On this basis, the recovery patterns of the post-fire forest are differentiated by considering the cumulative effect of fire, post-fire logging, and recovery approaches. The method is tested in the burn areas of the 5.6 Fire in the Greater Hinggan Mountain area (the largest forest fire in recorded history in China), giving an overall accuracy of 85% in post-fire forest logging mapping. Our results confirm that biological legacies (i.e. trees, logs, and snags) were removed across many areas in the fire, with activities peaking in the second year after the fire and located chiefly in areas of moderate and high burn severity. By identifying post-fire logging, the fluctuation and high disturbance index of the conventional temporal trajectory in the early stage of forest recovery are explained. The large-scale salvage logging slowed the recovery of the post-fire forest ecosystem and influenced the recovery process through the interaction of burn severity and active forest restoration. In areas of high burn severity, assisted natural regeneration (i.e. natural regeneration with artificial aids such as clearing the snags, weeding, digging pits, and supplemental planting) preserved biological legacies and achieved a higher proportion of forest recovery, second only to non-logged areas where natural regeneration (i.e. forestry recovering naturally without any artificial intervention) occurred. By contrast, salvage logging followed by artificial regeneration (i.e. clear-cutting all dead or damaged trees followed by tree planting or artificial seeding) hindered vegetation recovery in the early stage, but it improved the recovery rate in years 10–20 and approached the recovery proportion of non-logged areas where natural regeneration occurred as the recovery progressed and habitat conditions improved. The proposed method is shown to offer important advantages in detecting post-fire salvage logging, and it provides improved guidance for forest managers in developing strategies for forest recovery.

Root traits in response to frequent fires: Implications for belowground carbon dynamics in fire-prone savannas.

Predicting how belowground carbon storage reflects changes in aboveground vegetation biomass is an unresolved challenge in most ecosystems. This is especially true for fire-prone savannas, where frequent fires shape the fraction of carbon allocated to root traits for post-fire vegetation recovery. Here I review evidence on how root traits may respond to frequent fires and propose to leverage root traits to infer belowground carbon dynamics in fire-prone savannas. Evidently, we still lack an understanding of trade-offs in root acquisitive vs. conservative traits in response to frequent fires, nor have we determined which root traits are functionally important to mediate belowground carbon dynamics in a frequently burned environment. Focusing research efforts along these topics should improve our understanding of savanna carbon cycling under future changes in fire regimes.

Forest succession trajectories after fires in valleys and on slopes in the Greater Khingan Mountains, China

Accurate assessment of postfire vegetation recovery is important for forest management and the conservation of species diversity. Topography is an important factor affecting vegetation recovery but whether species composition varies with different recovery stages and between valleys and slopes is unclear. Using field data and a space-for-time substitution method, we quantified species richness and diversity to obtain the successional trajectories of valleys and slopes. We surveyed the species of 10 burned areas from 1986 to 2010 in the Greater Khingan Mountains in northeastern China, and found that with increasing postfire recovery time, species richness in both valleys and slopes gradually decreased. However, species richness in valleys was relatively higher. Shrubs recovered rapidly in the valleys, and species diversity maximized approximately 11 years after fire. However, it maximized 17–18 years after fire on the slopes. Numerous shade-tolerant species were present in the valleys 11 years after fire but not until after 18 years on slopes. Larch appeared earlier than 11 years after fire and its recovery was slow in the valleys but appeared quickly on slopes and established dominance early. Our study provides some new insights into vegetation succession after fire at local scales. After fire, the vegetation recovery processes differ with topography and it affects the initial rate of recovery and species composition at different successional stages.

Right-way fire in Australia's spinifex deserts: An approach for measuring management success when fire activity varies substantially through space and time

Indigenous Australians used fire in spinifex deserts for millennia. These practices mostly ceased following European colonisation, but many contemporary Indigenous groups seek to restore ‘right-way fire’ practices, to meet inter-related social, economic, cultural and biodiversity objectives. However, measuring and reporting on the fire pattern outcomes of management is challenging, because the spatio-temporal patterns of right-way fire are not clearly defined, and because spatio-temporal variability in rainfall makes fire occurrence highly variable in these desert environments. We present an approach for measuring and reporting on fire management outcomes to account for spatio-temporal rainfall variability. The purpose is to support Indigenous groups to assess performance against their management targets, and lay the groundwork for developing an accredited method for valuing combined social, cultural and biodiversity outcomes. We reviewed fire management plans of desert Indigenous groups to identify spatial fire pattern indicators for right-way fire in spinifex deserts. We integrated annual rainfall surfaces with time-since fire mapping (using Landsat imagery) to create a new spatial dataset of accumulated rainfall-since-last-fire, that better represents post-fire vegetation recovery as categorised by local Indigenous people. The fire pattern indicators were merged into a single score using an environmental accounting approach. To strengthen interpretation, we developed an approach for identifying a control area with matching vegetation and fire history, up to the point of management. We applied these methods to a 125,000 ha case study area: Durba Hills, managed by the Martu people of Western Australia. Using a 20-year time series, we show that since right-way fire management at Durba Hills was re-introduced (2009), the fire pattern indicators have improved compared to those in the matched control area, and the composite result is closer to the fine-scaled mosaic of right-way fire pattern targets. Our approach could be used by Indigenous groups to track performance, and inform annual fire management planning. As the indicators are standardised for rainfall variation, results from multiple sites can be aggregated to track changes in performance at larger scales. Finally, our approach could be adapted for other fire-prone areas, both in Australia and internationally with high spatio-temporal rainfall variability, to improve management planning and evaluation.