The dataset presented here was collected by the GenTree project (EU-Horizon 2020), which aims to improve the use of forest genetic resources across Europe by better understanding how trees adapt to their local environment. This dataset of individual tree-core characteristics including ring-width series and whole-core wood density was collected for seven ecologically and economically important European tree species: silver birch (Betula pendula), European beech (Fagus sylvatica), Norway spruce (Picea abies), European black poplar (Populus nigra), maritime pine (Pinus pinaster), Scots pine (Pinus sylvestris), and sessile oak (Quercus petraea). Tree-ring width measurements were obtained from 3600 trees in 142 populations and whole-core wood density was measured for 3098 trees in 125 populations. This dataset covers most of the geographical and climatic range occupied by the selected species. The potential use of it will be highly valuable for assessing ecological and evolutionary responses to environmental conditions as well as for model development and parameterization, to predict adaptability under climate change scenarios.

Sustainable territorial management requires reliable assessment of the impact of conservation policies on landscape structure and dynamics. Euro-Mediterranean regions present a remarkable biodiversity which is linked in part to traditional land use practices and which is currently threatened by global change. The effectiveness of one-decade conservation policies against land use changes was examined in Central Spain (Madrid Autonomous Community). A Markov model of landscape dynamics was parameterized with CORINE Land Cover information and transition matrices were obtained. The methods were applied in both protected and unprotected areas to examine whether the intensity and direction of key land use changes —urbanisation, agricultural intensification and land abandonment— differed significantly depending on the protection status of those areas. Protected areas experienced slower rates of agricultural intensification processes and faster rates of land abandonment, with respect to those which occurred in unprotected areas. It illustrates how simple mathematical tools and models —parameterized with available data— can provide to managers and policy makers useful indicators for conservation policy assessment and identification of land use transitions.

The potential productivity of forests is an important parameter in the evaluation of vegetation as a carbon sink. At the same time, potential productivity can be considered as an indicator of growth conditions and also as a measure of available fuel loads, which, in Mediterranean-type ecosystems, are a main factor of regional fire incidence. The present work deals with the relationship between an estimation of forest potential productivity and the fire incidence registered in peninsular Spain. Fire incidence was characterized by means of several fire regime variables. In order to contrast the patterns obtained, a similar analysis of the relationship between fire regime and human population density was also carried out. The results show that higher fire incidence was registered in more productive areas. Potential productivity was correlated to variables related to the number of fires and to the area burned, whereas the population density was also correlated to the number of fire variables and to the area burned, but with lower correlation coefficients. Although it is difficult to establish cause-and-effect relationships between complex phenomena that depend on a large number of factors, finding statistically significant relationships between fire incidence and the estimation of potential forest productivity used over a long time period is considered very relevant. These relationships make it necessary to take into account the fire regime when evaluating both forests and other terrestrial ecosystems as carbon sinks so as to meet the demands of the Kyoto Protocol.

Motivation: Trait variation within species can reveal plastic and/or genetic responses to environmental gradients, and may indicate where local adaptation has occurred. Here, we present a dataset of rangewide variation in leaf traits from seven of the most ecologically and economically important tree species in Europe. Sample collection and trait assessment are embedded in the GenTree project (EU‐Horizon 2020), which aims at characterizing the genetic and phenotypic variability of forest tree species to optimize the management and sustainable use of forest genetic resources. Our dataset captures substantial intra‐ and interspecific leaf phenotypic variability, and provides valuable information for studying the relationship between ecosystem functioning and trait variability of individuals, and the response and resilience of species to environmental changes.Main types of variable contained: We chose morphological and chemical characters linked to trade‐offs between acquisition and conservation of resources and water use, namely specific leaf area, leaf size, carbon and nitrogen content and their ratio, and the isotopic signature of stable isotope ¹³C and ¹⁵N in leaves.Spatial location and grain: We surveyed between 18 and 22 populations per species, 141 in total, across Europe.Time period: Leaf sampling took place between 2016 and 2017.Major taxa and level of measurement: We sampled at least 25 individuals in each population, 3,569 trees in total, and measured traits in 35,755 leaves from seven European tree species, i.e. the conifers Picea abies, Pinus pinaster and Pinus sylvestris, and the broadleaves Betula pendula, Fagus sylvatica, Populus nigra and Quercus petraea.Software format: The data files are in ASCII text, tab delimited, not compressed.