Drivers of persistent post-fire recruitment in European beech forests.

Climate change is expected to alter disturbance regimes including fires in European beech (Fagus sylvatica L.) forests. Regarding the resilience of beech forests to fire it is questionable whether seeds of this non-serotinous obligate masting seeder find advantageous conditions in a post-fire environment. The probability of recruitment success has been shown to increase when fire coincides with a mast year. However, the fire-induced recruitment window is poorly defined, and it is unclear how other interacting factors influence its duration. We used a space-for-time approach to model the relationships between post-fire beech recruitment, timing of seed mast events, and interacting environmental conditions using a zero-inflated model. Our results show that recruitment peaks 5-12 years after a fire, and continues throughout three decades post-fire. Beech recruitment in the post-fire period is driven by mast intensity interacting with (i) canopy opening as a consequence of progressive post-fire tree mortality and (ii) coverages of competing ground vegetation. Spring-summer moisture showed a weak positive effect on beech recruitment. We conclude that fires increase light availability, which in coincidence with a mast event results in pulses of beech recruitment. The delayed post-fire mortality of beech creates a recruitment window lasting for up to three decades, resulting in a higher-than-expected resilience of beech to individual fire disturbances.

Shallow landslide disposition in burnt European beech (Fagus sylvatica L.) forests.

Tree roots contribute significantly to soil strength on hillslopes. In the case of wildfires, this effect may abruptly vanish and be lacking for a considerable period of time depending on the resistance and resilience of the forest. Despite its importance, quantitative data on the impact and dynamics of wildfires on slope stabilization is still lacking. We use the study case of the Fagus sylvatica L. to quantify the medium-term evolution of root reinforcement and its effect on slope stability in fire-injured forests. In the study, we upscale root reinforcement using field data for the calibration of the Root Bundle Model and detailed information on forest structure in 244 plots, and calculate the spatio-temporal dynamics of forest protective capacity using a three-dimensional probabilistic slope stability model (slideforNET) for different site types. In unburnt and low-burn forests, the protective capacity was found to remain constant over time. Forests hit by moderate burns continue to provide adequate protection for shallow (depth < 0.5 m) and cohesive soils only, whereas in the case of high severity fires, the protective capacity vanishes for 15 years and an increased shallow landslide probability remains for at least 40 years. These conditions call for appropriate sylvicultural post-fire measures.

Inter-annual and decadal changes in teleconnections drive continental-scale synchronization of tree reproduction.

Climate teleconnections drive highly variable and synchronous seed production (masting) over large scales. Disentangling the effect of high-frequency (inter-annual variation) from low-frequency (decadal trends) components of climate oscillations will improve our understanding of masting as an ecosystem process. Using century-long observations on masting (the MASTREE database) and data on the Northern Atlantic Oscillation (NAO), we show that in the last 60 years both high-frequency summer and spring NAO, and low-frequency winter NAO components are highly correlated to continent-wide masting in European beech and Norway spruce. Relationships are weaker (non-stationary) in the early twentieth century. This finding improves our understanding on how climate variation affects large-scale synchronization of tree masting. Moreover, it supports the connection between proximate and ultimate causes of masting: indeed, large-scale features of atmospheric circulation coherently drive cues and resources for masting, as well as its evolutionary drivers, such as pollination efficiency, abundance of seed dispersers, and natural disturbance regimes.

Spatial patterns and broad-scale weather cues of beech mast seeding in Europe.

Mast seeding is a crucial population process in many tree species, but its spatio-temporal patterns and drivers at the continental scale remain unknown . Using a large dataset (8000 masting observations across Europe for years 1950-2014) we analysed the spatial pattern of masting across the entire geographical range of European beech, how it is influenced by precipitation, temperature and drought, and the temporal and spatial stability of masting-weather correlations. Beech masting exhibited a general distance-dependent synchronicity and a pattern structured in three broad geographical groups consistent with continental climate regimes. Spearman's correlations and logistic regression revealed a general pattern of beech masting correlating negatively with temperature in the summer 2 yr before masting, and positively with summer temperature 1 yr before masting (i.e. 2T model). The temperature difference between the two previous summers (DeltaT model) was also a good predictor. Moving correlation analysis applied to the longest eight chronologies (74-114 yr) revealed stable correlations between temperature and masting, confirming consistency in weather cues across space and time. These results confirm widespread dependency of masting on temperature and lend robustness to the attempts to reconstruct and predict mast years using temperature data.

Two centuries of masting data for European beech and Norway spruce across the European continent.

Tree masting is one of the most intensively studied ecological processes. It affects nutrient fluxes of trees, regeneration dynamics in forests, animal population densities, and ultimately influences ecosystem services. Despite a large volume of research focused on masting, its evolutionary ecology, spatial and temporal variability, and environmental drivers are still matter of debate. Understanding the proximate and ultimate causes of masting at broad spatial and temporal scales will enable us to predict tree reproductive strategies and their response to changing environment. Here we provide broad spatial (distribution range-wide) and temporal (century) masting data for the two main masting tree species in Europe, European beech (Fagus sylvatica L.) and Norway spruce (Picea abies (L.) H. Karst.). We collected masting data from a total of 359 sources through an extensive literature review and from unpublished surveys. The data set has a total of 1,747 series and 18,348 yearly observations from 28 countries and covering a time span of years 1677-2016 and 1791-2016 for beech and spruce, respectively. For each record, the following information is available: identification code; species; year of observation; proxy of masting (flower, pollen, fruit, seed, dendrochronological reconstructions); statistical data type (ordinal, continuous); data value; unit of measurement (only in case of continuous data); geographical location (country, Nomenclature of Units for Territorial Statistics NUTS-1 level, municipality, coordinates); first and last record year and related length; type of data source (field survey, peer reviewed scientific literature, gray literature, personal observation); source identification code; date when data were added to the database; comments. To provide a ready-to-use masting index we harmonized ordinal data into five classes. Furthermore, we computed an additional field where continuous series with length >4 yr where converted into a five classes ordinal index. To our knowledge, this is the most comprehensive published database on species-specific masting behavior. It is useful to study spatial and temporal patterns of masting and its proximate and ultimate causes, to refine studies based on tree-ring chronologies, to understand dynamics of animal species and pests vectored by these animals affecting human health, and it may serve as calibration-validation data for dynamic forest models.