The evaluation of vegetation cover after post-fire treatments of burned lands is important for forest managers to restore soil quality and plant biodiversity in burned ecosystems. Unfortunately, this evaluation may be time consuming and expensive, requiring much fieldwork for surveys. The use of remote sensing, which makes these evaluation activities quicker and easier, have rarely been carried out in the Mediterranean forests, subjected to wildfire and post-fire stabilization techniques. To fill this gap, this study evaluates the feasibility of satellite (using LANDSAT8 images) and drone surveys to evaluate changes in vegetation cover and composition after wildfire and two hillslope stabilization treatments (log erosion barriers, LEBs, and contour-felled log debris, CFDs) in a forest of Central Eastern Spain. Surveys by drone were able to detect the variability of vegetation cover among burned and unburned areas through the Visible Atmospherically Resistant Index (VARI), but gave unrealistic results when the effectiveness of a post-fire treatment must be evaluated. LANDSAT8 images may be instead misleading to evaluate the changes in land cover after wildfire and post-fire treatments, due to the lack of correlation between VARI and vegetation cover. The spatial analysis has shown that: (i) the post-fire restoration strategy of landscape managers that have prioritized steeper slopes for treatments was successful; (ii) vegetation growth, at least in the experimental conditions, played a limited influence on soil surface conditions, since no significant increases in terrain roughness were detected in treated areas.

After wildfires, emergency actions and post-fire management are implemented to mitigate fire damage. Salvage logging is a tool often applied to burned stands, but despite being a post-fire forest management tool to restore ecosystem functions, its ecological effects remain poorly understood. In the Mediterranean Basin, where land use and land-use change are bringing about changes in drought periods and fire regimes, optimal treatments should be included in adaptive management in order to increase resilience and reduce vulnerability. In July 2012, a mid- to high-burn severity fire burned almost 7000 ha of an Aleppo pine forest (Pinus halepensis Mill.) in southeastern Spain. Five years later (late spring 2017), we designed an experimental study to monitor four stand categories on a burn severity basis (unburned mature stands, low-burn severity stands, and high-burn severity stands) and a salvage logging operation carried out 6 months after the fire in high-burn severity areas. We set 60 circular plots (15 in each treatment scenario) and 180 linear transects (3 per plot, 45 per scenario) to check the ecological facilitation of pine trees and snags (canopy size and/or perch effect). We estimated plant alpha diversity (floristic richness, abundance and dominance indices) and post-fire plant recovery (pine recruitment and adaptive traits). Fire depleted the system’s diversity, but in low-severity burning areas some basic functions remained intact (e.g., soil protection). We found that high-burn severity very negatively impacted ecosystem functions through the removal of duff and litter leaving unprotected soil. Collecting wood reduced pine regeneration and growth, which was considerable in the areas that suffered high-burn severity. The burned snags did not appear to act as perches resulting in seed dispersal. Obligate seeders were determined to be an efficient strategy for facing high-severity fires, whereas resprouters response showed no clear burn severity pattern despite being present in all the scenarios. Therefore, salvage logging did not affect the recovery of some ecosystem properties/features (such as plant total cover or litter cover), although retaining dead pines facilitated pine regeneration. Thus, leaving snags in areas affected by high-burn severity in ecosystems mainly modelled by fires is proposed. However, the ecosystem response could be widely variable and influenced by local abiotic factors, so restoration might not be as effective as in the current proposal.

Forest fires and post‐fire practices influence sediment connectivity (SC). In this study, we use the ‘aggregated index of connectivity’ (AIC) to assess SC in five Mediterranean catchments (198–1090 ha) affected by a wildfire in 2012 in south‐eastern Spain. Two temporal scenarios were considered, immediately after the fire and before post‐fire management, and 2 years after the fire including all practices (hillslope barriers, check‐dams, afforestation, salvage logging and skid trails). One LiDAR (light detection and ranging)‐derived digital elevation model (DEM, 2 m × 2 m resolution) was generated, per scenario. The five catchment outlets were established as the computation target (AIC_OUT), and structural and functional SC were calculated. Index outputs were normalized to make the results of the non‐nested catchments comparable (AIC_N‐OUT). The output analysis includes the SC distribution along the catchments and at local scale (929 sub‐catchments, 677 in the burned area), the hillslope and channel measures' effect on SC, and a sedimentological analysis using observed area‐specific sediment yield (SSY) at 10 new (built after post‐fire practices) concrete check‐dams located in the catchments (SSY = 1.94 Mg ha⁻¹ yr⁻¹; σ = 1.22). The catchments with more circular shapes and steeper slopes were those with higher AIC_N‐OUT. The structural SC maps – removing the rainfall erosivity influence – allowed evaluating the actual role played by the post‐fire practices that reduced SC ( = − 1.19%; σ = 0.41); while functional SC was linked to the actual change of SC ( = + 5.32%; σ = 0.62). Hillslope treatments resulted in significant changes on AIC_N‐OUT at sub‐catchment scale with certain disconnectivity. A good and positive correlation was found between the SSY and the changes of AIC_N‐OUT. However, the coarse DEM resolution explained the lack of effect of the rock check‐dams – located on the secondary channels – on AIC_N‐OUT. AIC_N‐OUT proved to be a useful tool for decision making in post‐fire restoration, but an optimal input data is still necessary to refine calculations.

The modification of fire regimes and their impact on vegetation recovery, soil properties, and fuel structure are current key research areas that attempt to identify the thresholds of vegetation’s susceptibility to wildfires. This study aimed to evaluate the vulnerability of Mediterranean pine forests (Pinus halepensis Mill. and Pinus pinaster Aiton) to wildfires, analyzing two major forest fires that occurred in Yeste (Spain) in 1994 and 2017, affecting over 14,000 and 3200 hectares, respectively. Four recovery regions were identified based on fire severity—calculated using the delta Normalized Burn Ratio (dNBR) index—and recurrence: areas with high severity in 2017 but not in 1994 (UB94-HS17), areas with high severity in 1994 but not in 2017 (HS94-UB17), areas with high severity in both fires (HS94-HS17), and areas unaffected by either fire (UB94-UB17). The analysis focused on examining the recovery patterns of three spectral indices—the Normalized Difference Vegetation Index (NDVI), Normalized Moisture Index (NDMI), and Normalized Burn Ratio (NBR)—using the Google Earth Engine platform from 1990 to 2023. Additionally, the Relative Recovery Indicator (RRI), the Ratio of Eighty Percent (R80P), and the Year-on-Year average (YrYr) metrics were computed to assess the spectral recovery rates by region. These three spectral indices showed similar dynamic responses to fire. However, the Mann–Kendall and unit root statistical tests revealed that the NDVI and NDMI exhibited distinct trends, particularly in areas with recurrence (HS94-HS17). The NDVI outperformed the NBR and NDMI in distinguishing variations among regions. These results suggest accelerated vegetation spectral regrowth in the short term. The Vegetation Recovery Capacity After Fire (VRAF) index showed values from low to moderate, while the Vulnerability to Fire (V2FIRE) index exhibited values from medium to high across all recovery regions. These findings enhance our understanding of how vegetation recovers from fire and how vulnerable it is to fire.

Forest fires intensify sediment transport and aggravate local and off-site consequences of soil erosion. This study evaluates the influence of post-fire measures on structural and functional sediment connectivity (SC) in five fire-affected Mediterranean catchments, which include 929 sub-catchments, by using the "aggregated index of connectivity" (AIC) at two temporal scenarios: I) immediately after the fire and before implementing post-fire practices ('Pre-man'), and II) two years after the fire ('Post-man'). The latter includes all the emergency stabilization practices, that are hillslope barriers, check-dams and afforestation. The stream system was set as the target of the computation (STR), to be representative of intense rainfall-runoff events with effective sediment delivery outside the catchments. Output normalization (AIC_N) allows comparing the results of the five basins between them. The sedimentological analysis is based on specific sediment yield (SSY) -measured at the check-dams installed after the fire -, and this data is used for output evaluation. Stream density and slope variables were the most influential factors on AIC_N-STR results at the sub-catchment scale. Post-fire hillslope treatments (barriers when built in high densities and afforestation) significantly reduced AIC_N-STR in comparison with untreated areas in both structural and functional approaches. Despite the presence of hillslope treatments, the higher erosive rainfall conditions resulted in higher AIC_N-STR values in the Post-man scenario (functional approach). A positive and good correlation was found between the measured SSY and the AIC_N-STR changes due to the post-fire practices and vegetation recovery, showing the good correspondence of the computation results and the real sediment dynamics of the studied catchments. Overall, AIC_N demonstrated to be a useful and versatile tool for post-fire management, which needs further research to optimize its applicability.