When managing degraded ecosystems the objective is to restore them to normal functioning ( Holmes & Richardson 1999 ), and therefore restoration and conservation activities must be considered complementary. In afforestation and restoration activities, one of the main concerns is the use of a suitable species pool ( Jones, 2003 ), i.e. the set of species that can potentially inhabit a site with the local ecological conditions ( Zobel et al. , 1998 ; Pärtel et al. , 2011 ; García del Barrio et al. , 2013 ). A special emphasis is being paid to plant species diversification, which involves a better use of the large pool of native species available when using an ecosystem-oriented approach ( Bautista et al. , 2009 ). In most cases, it is local species that are promoted, according to basic principles of restoration ecology ( Anonymous, 2007 ) aim towards carbon sequestration and reduction of net CO ₂ emissions. Local adaptation has been invoked for the use of local material ( Mckay et al ., 2005 ). However, it has been stated that it is seldom the ideal solution ( Jones & Monaco, 2009 ) in degraded or non-productive areas, and that their role is still unclear ( e.g _. the role of local provenance in reintroductions ( Sutherland et al. _, 2006 ).

Forecasting the performance of forest species used in restoration and conservation activities rely on their intra-specific variability ( Langlet, 1971 ; Van Andel, 1998 ). Due to the importance of this inter-population differentiation, the core marketing unit of source-identified forest reproductive materials in the certification schemes is the region of provenance, or seed zone ( Nanson, 2001 ). Therefore knowing populations differences both in their levels of diversity for neutral markers and in the variability for important adaptive and performance traits ( e.g. growth, tolerance to biotic and abiotic stresses) are essential in afforestation and restoration activities ( Alía et al ., 2009b ).

Research has reinforced the idea that the forest material supplied for native woodland creation and restoration should come from a seed source that is both genetically and ecologically proper for the planting site ( Mckay et al ., 2005 ; Leimu & Fischer, 2008 ; Vander-Mijnsbruggea, 2010 ; Sgrò et al ., 2011 ; Breed et al ., 2012 ; Bucharova et al ., 2016 ), and also would be adapted to the future climatic conditions ( Konnert et al ., 2015 ). Considering conservation activities, in particular when managing conservation units or reinforcement activities, the origin of the material is also crucial, as genetic introgression and/or gene flow risk with undesirable origins or non-local material is a big concern for natural populations and their regeneration ( Moritz, 1994 ; Moritz, 1999 ; Robledo-Arnuncio et al ., 2009 ; Steinitz et al ., 2012 ). Taking into consideration the origin of forest reproductive material is essential for the conservation of forest genetic resources ( Koskela et al ., 2013 ), e.g. when determining the gene pool that can be used in the vicinities of conservation units ( Mckay et al ., 2005 ).

In all these cases, the possibility of checking the origin of the material is essential for an effective control of the marketing of the material used in restoration and conservation activities. Forest tree species present low levels of breeding, and it is hard to have reliable fingerprinting methods to control the use of the correct reproductive material at the population level, or to avoid marketing fraud (Nanson 2001; Degen et al ., 2010 ), despite its extensive use. Some attempts to identify forest reproductive material have been applied to specific materials in pine species ( Aragonés et al ., 1997 ; Ribeiro et al ., 2002 ; Deguilloux et al ., 2004 ; Tigabu et al ., 2005 ; Fidler et al ., 2006 ), and also different DNA fingerprinting approaches have been implemented to assign material in Quercus robur L. ( Degen et al ., 2010 ), following methods already in use for other organisms ( Honjo et al ., 2008 ). Also, some methods for origin traceability are being implemented in important tropical timber species ( Tnah et al ., 2009 ; Degen et al ., 2010 ; Hong et al ., 2010 ).

Different approaches have been used to identify gene pools based on genetic markers. Especially those derived from Bayesian approaches ( e.g. Pritchard et al ., 2000 ; Dupanloup et al ., 2002 ). However, these approaches usually group populations with contrasting performance in quantitative or adaptive traits ( González-Martínez et al ., 2004 ), and also from different regions of provenance and therefore marketing units.

Extensive studies using chloroplast microsatellites (cpSSRs) covering the distribution range of different species are now available ( e.g. Soranzo et al ., 2000 ; Gómez et al ., 2005 ; Bucci et al ., 2007 ; Heuertz et al ., 2010 ) . Therefore, it would be interesting to test if these markers constitute a reliable tool for the identification of material to be used in restoration and conservation activities. To our knowledge, there is not an attempt to use extensive information on the geographic variation of forest tree species to test whether it is possible to differentiate among different regions of provenance for important groups of forest species.

We tested here the identification of populations of various pine species with contrasting levels of differentiation ( Soto et al ., 2010 ), as an example for the use of extensive marker datasets of populations that are becoming available ( e.g .: (GD) ² Database: https://gd2.pierroton.inra.fr/gd2/login/login , Demiur-ge database: http://www.demiurge-project.org/ ). The species considered were Pinus halepensis Mill., Pinus pinaster Ait., Pinus nigra Arn. subsp. salzamanni (Dunal) Franco, Pinus sylvestris L., and Pinus uncinata Ram. Forest tree species play an essential role in determining many ecosystem properties and also influence the genetic diversity of associated organisms ( Whitham et al ., 2006 ). These species are highly relevant in Europe and along the Mediterranean region as they are broadly used in afforestation, restoration and conservation programs. Moreover, extensive studies on the genetic variation of the species have been done ( P. halepensis : Morgante et al ., 1996 ; P. pinaster . Vendramin et al ., 1998 ; P. pinaster : Bucci et al ., 2007 ; P. halepensis : Grivet et al ., 2009 , 2013 ; P. pinaster and P. sylvestris : Soto et al ., 2010 ; Unger et al ., 2014 ), and reveal contrasting levels of variation using cpSSR markers. We used haploid cpSSR genetic markers to check the assignation of populations to different groups with application in afforestation, restoration and conservation activities.

We applied the methods to the regions of provenance of the species in the Spanish Iberian Peninsula. The area has a particular climatic regime of cold, wet winters and hot, dry summers, and a long history of human activity, grazing pressure, and fires ( Valbuena-Carabaña et al ., 2009 ). Also, reforestation and afforestation activities have a long tradition with more than 2.2 million of hectares reforested with these pine species, and representing the 74% of the total reforested area during the period 1940-1995 ( Montero, 1997 ).

Firstly, we grouped populations for each species with use in afforestation and conservation programs ( Alía et al ., 2009b ). Secondly, we tested the probability of assignment of different samples to the different groups, based on the S genetic distance ( Ribeiro et al ., 2002 ) using a Monte Carlo method among each population and the implemented reference groups through a novel software (Blue Caterpillar).

All the pine studied species exhibited high rates of differentiation among populations (Table 2), except for P. halepensis . Using the analysis of molecular variance (AMOVA), it was possible to distinguish different groups that ranged form three to ten depending on the species.

Those groups were subdivided according to their distinct purpose (afforestation and restoration or conservation) (Table 1). Some of the groups included only one population (8 out of 10 in P. halepensis , 12 out of 17 in P. pinaster , 5 out of 10 in P. nigra , 4 out of 12 in P. sylvestris and 3 out of 4 in P. uncinata ), with most of those populations defined as important in conservation programs.

An assignment summary of either conservation and restoration or afforestation populations into the different genetic groups are presented in Table 3. The species with the highest rates of success in assignment were P. sylvestris and P. uncinata , and the one with lowest rate was P. halepensis . In any case, all the species, except P. halepensis , present high rates of correct assignments (> 80 %). It is interesting to notice that conservation populations were correctly assigned in most of the cases for all the species.

However, considering that the assignment was correct in most of the cases, it is noteworthy the case of P. halepensis and P. sylvestris where many groups are genetically close (Table 4) and, therefore, it could bias the assignment success rate.

The five Spanish pine species used in this paper exhibit, due to their mating systems, a large level of genetic diversity within populations and a low to intermediate level of differentiation among populations ( Soto et al ., 2010 ). These features are known to improve resilience, productivity and recovery from climate extremes and give stability to the ecosystem, therefore being a key issue on the use of forest reproductive material and conservation programs of the species ( Thomson et al ., 2009 ; Isbell et al ., 2011 ; Alfaro et al ., 2014 ).

We present an approach that can assign the origin of material that could be used in afforestation, restoration or conservation activities which are essential in managing the forest genetic resources. The findings showed that the method worked well for two species, P. sylvestris and P. uncinata , for another two, P. nigra and P. pinaster , with an exit of assignment over an 85%, being P. halepensis the species with the lowest rate of identification. It is noteworthy to say this is the first method that can verify the origin of those species, as research has proven to identify specific populations ( Ribeiro et al ., 2002 ; Robledo-Arnuncio et al ., 2009 ), or has been used in the delineation of genetic zones of interest in breeding and conservation activities ( Bucci and Vendramin 2000 ; Bucci et al ., 2007 ). Other methods have been developed based in the identification of both the adult population and the material obtained from it ( Deguilloux et al ., 2004 ; Degen et al ., 2010 ).

Although afforestation and restoration activities with these species are usually based on local material, which refers to the same region of provenance, in species with large spatial structure, local material can differ even at short distances. However, in our study the extensive gene flow allows to consider more extensive populations. We could not clearly differentiate populations from some regions of provenance ( e.g . in P. halepensis ) showing that only some groups of populations could be distinguished but also, we found that in some cases populations from the same region of provenance were different. Regions of provenance have been defined mostly based on ecological and extensive genetic information ( Gil et al ., 1996 ). Information from genetic markers is not the best option to define regions with a similar pattern of variation in traits related to adaptation or growth ( e.g ., Hamann et al ., 2000 ), therefore redefinition of the limits of some regions of provenance might be needed.

The European Forest Genetic Resource Program ( EUFORGEN ) has defined different in-situ conservation units of the species, and the conservation program ( Jimenez et al ., 2009 ; Koskela et al ., 2013 ) includes the definition of genetic criteria for restoration activities and for monitoring the conservation units ( Aravanopoulos 2011 ; Graudal et al ., 2014 ; Fussi et al ., 2016 ). In our case, we could distinguish almost all the conservation populations considered in the study that will allow a better implementation of activities in Spain.

We demonstrated the usefulness of extensive markers datasets that are becoming available for identification of gene pools at the population level in different species. Nevertheless, results depend on factors such as the genetic diversity and the differentiation within and between populations. The rate of successful identification of populations among the different species was very high (> 94 %) for P. nigra , P. sylvestris and P. uncinata , high (circa 85 %) for P. pinaster , and low (< 79 %) for P. halepensis . More information is needed in P. halepensis and for some areas in P. pinaster .

We are grateful to the INIA marker database GENFODAT (A. Gómez, A. Soto de Viana, S.C. Gonzalez-Martínez, J.J. Robledo-Arnuncio, P. Jimenez, D. Barba, C. Garcia) for providing the information of the populations. The text has been revised by a professional in English grammar and style, P. C. Grant.