The NERC and CEH trademarks and logos ('the Trademarks') are registered trademarks of NERC in the UK and other countries, and may not be used without the prior written consent of the Trademark owner. 1 Evolution-based approach needed for the conservation and silviculture of peripheral forest tree populations

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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 5 th 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. Citation: Marchi M, Ducci F (2018). Some refinements on species distribution models using tree-level National Forest Inventories for supporting forest management and marginal forest population detection. iForest

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Aim of the 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 species Area of study: A rear-edge marginal population of Pinus nigra spp. nigra in Abruzzo region, central Italian Apennines Matherials 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 favour 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.

Silver fir (Abies alba) is a common tree species in the mountainous areas in Europe. A number of natural stands in the hilly regions of northern Europe represent relic populations. The aim of the research was to evaluate the diversity present in Italian populations of the species. Genetic diversity was assessed in 45 silver fir populations covering the species' distribution range in Italy, based on the allelic variation present at seven microsatellite loci (SSRs). A consistent level of intra-population variability was present. Several of the populations displayed signs of ongoing genetic erosion, and evidence for a recent bottleneck in some was identified. Populations from the eastern Alps and the Apennines were more variable than those sampled from the western Alps. About 8% of the overall genetic variance was found between populations, with the remainder representing variation present within the populations. The data suggested that the southern Apennines acted as a refugium during the most recent Ice Age, and that many of the populations from this area have remained isolated over a prolonged period. Smaller and more isolated populations have experienced genetic drift, whereas the larger ones have preserved a high level of diversity. Identification of genetically homogeneous regions could be informative for the management of genetic resources.