Investigating the relationship between climate, stand age, and temporal trends in masting behavior of European forest trees.

Masting-temporally variable seed production with high spatial synchrony-is a pervasive strategy in wind-pollinated trees that is hypothesized to be vulnerable to climate change due to its correlation with variability in abiotic conditions. Recent work suggests that aging may also have strong effects on seed production patterns of trees, but this potential confounding factor has not been considered in previous times series analysis of climate change effects. Using a 54 year dataset for seven dominant species in 17 forests across Poland, we used the proportion of seed-producing trees (PST) to contrast the predictions of the climate change and aging hypotheses in Abies alba, Fagus sylvatica, Larix decidua, Picea abies, Pinus sylvestris, Quercus petraea, and Quercus robur. Our results show that in all species, PST increased over time and that this change correlated most strongly with stand age, while the standardized precipitation-evapotranspiration index, a measure of drought, contributed to temporal trends in PST of F. sylvatica and Q. robur. Temporal variability of PST also increased over time in all species except P. sylvestris, while trends in temporal autocorrelation and among-stand synchrony reflect species-specific masting strategies. Our results suggest a pivotal role of plant ontogeny in driving not only the extent but also variability and synchrony of reproduction in temperate forest trees. In a time of increasing forest regrowth in Europe, we therefore call for increased attention to demographic effects such as aging on plant reproductive behavior, particularly in studies examining global change effects using long-term time series data.

Masting in wind-pollinated trees: system-specific roles of weather and pollination dynamics in driving seed production.

Masting, the highly variable production of synchronized large seed crops, is a common reproductive strategy in plant populations. In wind-pollinated trees, flowering and pollination dynamics are hypothesized to provide the mechanistic link for the well-known relationship between weather and population-level seed production. Several hypotheses make predictions about the effect of weather on annual pollination success. The pollen coupling hypothesis predicts that weather and plant resources drive the flowering effort of trees, which directly translates into the size of seed crops through efficient pollination. In contrast, the pollination Moran effect hypothesis predicts that weather affects pollination efficiency, leading to occasional bumper crops. Furthermore, the recently formulated phenology synchrony hypothesis predicts that Moran effects can arise because of weather effects on flowering synchrony, which, in turn, drives pollination efficiency. We investigated the relationship between weather, airborne pollen, and seed production in common European trees, two oak species (Quercus petraea and Q. robur) and beech (Fagus sylvatica) with a 19-yr data set from three sites in Poland. Our results show that warm summers preceding flowering correlated with high pollen abundance and warm springs resulted in short pollen seasons (i.e., high flowering synchrony) for all three species. Pollen abundance was the best predictor for seed crops in beech, as predicted under pollen coupling. In oaks, short pollen seasons, rather than pollen abundance, correlated with large seed crops, providing support for the pollination Moran effect and phenology synchrony hypotheses. Fundamentally different mechanisms may therefore drive masting in species of the family Fagacae.

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.