Natural Regeneration of Maritime Pine: A Review of the Influencing Factors and Proposals for Management

A method to produce a flexible and customized fuel models dataset

Simulation of vegetation fires very often resorts to fire-behavior models that need fuel models as input. The lack of fuel models is a common problem for researchers and fire managers because its quality depends on the quality/availability of data. In this study we present a method that combines expert- and research-based knowledge with several sources of data (e.g. satellite and fieldwork) to produce customized fuel models maps. Fuel model classes are assigned to land cover types to produce a basemap, which is then updated using empirical and user-defined rules. This method produces a map of surface fuel models as detailed as possible. It is reproducible, and its flexibility relies on juxtaposing independent spatial datasets, depending on their quality or availability. This method is developed in a ModelBuilder/ArcGis toolbox named FUMOD that integrates ten sub-models. FUMOD has been used to map the Portuguese annual fuel models grids since 2019, supporting regional fire risk assessments and suppression decisions. Datasets, models and supplementary files are available in a repository (https://github.com/anasa30/PT_FuelModels). •FUMOD is a flexible toolbox with ten sub-models included that maps updated Portuguese fuel models.

Ecological niche models applied to post-megafire vegetation restoration in the context of climate change

Climate change and land-use changes are the main drivers altering fire regimes and leading to the occurrence of megafires. Current management policies mainly focus on short-term restoration without considering how climate change might affect regeneration dynamics. We aimed to test the usefulness of ecological niche models (ENMs) to integrate the effects of climate change on tree species distributions into post-fire restoration planning. We also examined different important conceptual and methodological aspects during this novel process. We constructed ENM at fine spatial resolution (25 m) for the four main tree species (Pinus pinaster, Quercus pyrenaica, Q. faginea and Q. ilex) in an area affected by a megafire in Central Spain at two scales (local and regional), two periods (2 and 14 years after the fire) at the local scale, and under two future climate change scenarios. The usefulness of ENMs as support tools in decision-making for post-fire management was confirmed for the first time. As hypothesized, models developed at both scales are different, since they represent different scale dependent drivers of species distribution patterns. However, both provide objective information to be considered by stakeholders in combination with other sources of information. Local models generated with vegetation data 14 years after the fire provided valuable information about local and current vegetation dynamics (i.e., current microecology spatial niche prediction). Regional models are capable of considering a higher proportion of the climatic niche of species to generate reliable climate change forecasts (i.e., future macroclimate spatial niche forecast). The use of precise ENMs provide both an objective interpretation of potential habitat conditions and the opportunity of examining vegetation patches, that can be very valuable in managing restoration of areas affected by megafires under climate change conditions.

Quality Assessment and Rehabilitation of Mountain Forest in the Chongli Winter Olympic Games Area, China

Spurred by the degraded forest in the 2022 Chongli Winter Olympic Games area, the Chinese government initiated a national program for mountain forest rehabilitation. We developed a method to assess the quality of mountain forests using an index system composed of stand structure, site conditions, and landscape aesthetics at three criteria levels. The method involves index weights determined by the analytical hierarchy process (AHP) and entropy method. The results show that landscape aesthetics was the most important measure for the criterion layer. Slope aspect and naturalness were the most and second-most important indices, respectively, for the alternative layer. The quality of the mountain forest in the Chongli area was divided into four grades. The area had 7.8% with high quality, 46.7% with medium quality, 36.6% with low quality, and 8.9% with inferior quality. In total 76.6% of the damaged forest were distributed on sloping and steep sloping ground at 1700 to 2050 m altitude, and Betula platyphylla Sukaczev and Larix gmelinii var. principis-rupprechtii (Mayr) Pilg. were the predominating trees. The damaged forest was divided into over-dense, over-sparse, degraded, inappropriate tree species, and inferior landscape forest. For different types of damaged forest, corresponding modification measures were proposed. The methods developed in this study can be used for rehabilitation projects to improve the quality of degraded forests in mountainous temperate areas.