Marco Conedera, Peter Thomas, Burkhard Beudert, Davide Ascoli, Marjana Westergren, Renzo Motta, Giorgio Vacchiano, Luc Croisé, Silvio Schueler, Rolf Övergaard, Igor Drobyshev, Anton Burkart, Christian Zang, Mara Cirolli, Pietro Piussi, Ciprian Palaghianu, Janet Maringer, Władysław Kantorowicz, Jonathan G.A. Lageard, Andrew Hacket-Pain, Regula Gehrig Bichsel, Roberta Berretti, Apollo - University of Cambridge Repository, Ascoli, Davide, Maringer, Janet, Hacket Pain, Andy, Conedera, Marco, Drobyshev, Igor, Motta, Renzo, Cirolli, Mara, Kantorowicz, Władysław, Zang, Christian, Schueler, Silvio, Croisé, Luc, Piussi, Pietro, Berretti, Roberta, Palaghianu, Ciprian, Westergren, Marjana, Lageard, Jonathan G. A, Burkart, Anton, Bichsel, Regula Gehrig, Thomas, Peter A, Beudert, Burkhard, Övergaard, Rolf, and Vacchiano, Giorgio
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 We collected masting data from a total of 359 sources through an extensive literature review and from unpublished surveys.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 dataset has a total of 1747 series and 18348 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, grey 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 years where converted into a five classes ordinal index. To our knowledge, this is the most comprehensive published database on species-specific masting behaviour. 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. This article is protected by copyright. All rights reserved.