• Energy Research

Abies alba, Abies marocana, Acer monspessulanum, Acer obtusifolium, Acer opalus, Alnus cordata, Alnus glutinosa, Arbutus andrachne, Arbutus unedo, Betula pendula, Carpinus betulus, Castanea sativa, Cedrus brevifolia, Cedrus atlantica, Cretagus azarolus, Cupressus atlantica, Elaeagnus, angustifolia, Fagus sylvatica, Fraxinus angustifolia, Fraxinus excelsior, Fraxinus ornus, Fraxinus syriaca, Juglans regia, Juniperus deltoides, Juniperus drupacea, Juniperus phoenicea, Juniperus turbinata, Larix decidua, Picea abies, Pinus brutia, Pinus cembra, Pinus halepensis, Pinus heldreichii, Pinus mugo, Pinus nigra, Pinus peuce, Pinus pinaster, Pinus pinea, Pinus sylvestris, Platanus orientalis, Populus nigra, Populus tremula, Prunus avium, Quercus boisierri, Quercus calliprinos, Quercus cerris, Quercus frainetto, Quercus ilex, Quercus ithaburensis, Quercus look, Quercus petraea, Quercus pubescens, Quercus pyrenaica, Quecus robur, Quercus trojana, Salix alba, Salix phylicifolia, Sorbus torminalis, Ulmus glabra, Ulmus laevis, Ulmus pumila, Ulmus canecens This dataset is the result of a survey conducted during the 2012-2016 COST Action FP1202 (MaP-FGR): Strengthening conservation: a key issue for adaptation of marginal/peripheral populations of forest trees to climate change in Europe. It contains the name, location and other relevant information of 577 forests that are considered as marginal of peripheral by forest experts. Information (as specified in the read-me file) includes among others: Genus, Species, Country, Name of marginal population, Latitude, Longitude, Elevation, Type of marginality, Silvicultural system, Protection status, Threat status, and genetic and phenotypic trait data availability This dataset can be used to, e.g., test effects of marginality on biological and genetic traits, compare expert knowledge with statistics-based indicators, raise awareness of the importance of marginal populations for conservation and sustainable use.

The fate of peripheral forest tree populations is of particular interest in the context of climate change. These populations may concurrently be those where the most significant evolutionary changes will occur ; those most facing increasing extinction risk ; the source of migrants for the colonization of new areas at leading edges ; or the source of genetic novelty for reinforcing standing genetic variation in various parts of the range. Deciding which strategy to implement for conserving and sustainably using the genetic resources of peripheral forest tree populations is a challenge. Here, we review the genetic and ecological processes acting on different types of peripheral populations and indicate why these processes may be of general interest for adapting forests and forest management to climate change. We particularly focus on peripheral populations at the rear edge of species distributions where environmental challenges are or will become most acute. We argue that peripheral forest tree populations are ‘‘natural laboratories” for resolving priority research questions such as how the complex interaction between demographic processes and natural selection shape local adaptation ; and whether genetic adaptation will be sufficient to allow the long-term persistence of species within their current distribution. Peripheral populations are key assets for adaptive forestry which need specific measures for their preservation. The traditionally opposing views which may exist between conservation planning and sustainable forestry need to be reconciled and harmonized for managing peripheral populations. Based on existing knowledge, we suggest approaches and principles which may be used for the management and conservation of these distinctive and valuable populations, to maintain active genetic and ecological processes that have sustained them over time.

Spatial modelling is a fundamental tool to support forest management strategies. National Forest Inventories (NFIs) provide extensive and detailed data for spatial analysis. In this study, the most recent Italian NFI (INFC2005) was used to evaluate possible refinements on species distribution model (SDM) techniques and to derive the future scenarios for two target species (Fagus sylvatica L. and Abies alba Mill.) sharing a similar ecological environment and geographic range. A weighted SDM and a provenance distribution model (PDM) were tested, based on tree-level selection of NFI plots using species basal area as a filter. Two climate projections were analysed for 2050s according to the IPCC 5th Assessment Report (AR5). The results were evaluated as possible guidelines for management of the Italian region of the EUFGIS network, where many marginal forest populations (MaPs) are currently included as genetic conservation units (GCUs). The uncertainty of coordinates of inventory points did not affect the results of SDM. No statistical differences were found when comparing the niche realization for the two model species (ANOVA p>0.05) mainly due to spatial autocorrelation between the environmental predictors. Based on the classic SDM evaluation method (True Skill Statistic - TSS) little improvements in predictions were observed when weighting each presence/absence records, possibly due to the lack of adequate ancillary data but also to the evaluation method. A higher accuracy of predictions (TSS>0.85) was obtained when different "provenances" were modelled separately, due to the reduction in the "background noise". We showed that for classical SDM, the prevalence of certain ecological features of some locations may drive algorithms to produce coarse averaged predictions. Provenance distribution modelling may represent a valuable step forward in spatial analysis, particularly for the detection of marginal peripheral populations. The exact spatial co-ordinates of plots and additional information on site quality (e.g., stand age, site index, etc.) in NFI data could greatly help in better weighting presence/absence data and properly test the new evaluation methods.

Aim of study: To forecast the effects of climate change on the spatial distribution of Black pine of Villetta Barrea in its natural range and to define a possible conservation strategy for the speciesArea of study: A rear-edge marginal population of Pinus nigra spp. nigra in Abruzzo region, central Italian ApenninesMatherials and Methods: For its adaptive and genetic traits this population is considered endemic of the Italian peninsula and represents a rear-edge marginal population of nigra subspecies. The spatial distribution of the tree in the administrative Region (Abruzzo) was used to define the ecological traits while three modelling techniques (GLM, GAM, Random Forest) were used to build a Species distribution model according to two climatic scenarios.Main results: The marginal population's range was predicted to shift at higher elevations as consequence of climatic adaptation. Many zones, represented by the higher part of the mountains surrounding the study area (currently bare and inhospitable for trees), were identified as suitable in future for the species. However, in the case of a rapid climate change, this marginal population may not be able to move as fast as necessary. An in-situ adaptive management integrated with an assisted migration protocol might be considered to enforce the natural regeneration and improve the richness and variability of the genetic pool.Research highlights: Most of the genetic richness is held in small populations at the borders of natural distribution of forest species. Monitoring this MAP could be useful to understand the adaptive processes of the species and could support the future management of many other within-core populations.Keywords: Species Distribution Models; Mediterranean forests; Abruzzo; climate change; altitudinal shift.