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ZENODO
Dataset . 2022
License: CC BY
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
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Dataset of Local seed sourcing strategies in Spain

Authors: Francisco J. Auñon; David Sanchez de Ron; Eduardo Notivol; Jose M. Garcia del Barrio; Ricardo Alia;

Dataset of Local seed sourcing strategies in Spain

Abstract

Strict-sense local seed-sourcing strategy (SSL) was defined for each deployment zone as the use of autochthonous populations pertaining to the same region of provenance for each species. Wide-sense local seed-sourcing strategy (WSL) was defined as the use of the pool of regions of provenance with a suitable climatic niche in each zone. Niche modelling was used to obtain the climate-predicted distribution of the species based on the actual presence and the climate (assuming no restrictions to dispersal and no human influence). Nine climatic variables were considered: mean annual (P), winter (WP), and summer (SP) precipitation, mean annual temperature (T), minimum temperature of the coldest month (MTC), maximum temperature of the warmest month (MTW), growing degree days (t>5°) (DD), total number of months under frost (t<0º) (F), duration of the drought period in months (P<2T) (DP). These variables have been used for modelling niche distribution of different forest species in Spain. A similarity index was obtained based on the Mahalanobis climatic distance (using the same set of climatic variables that in the niche modelling estimation, among the points with presence of the region of provenances and the points of each deployment zone. Based on this similarity the regions of provenance were classified as suitable or not for each deployment zone.

This research was supported by the Project AEG 17-048 established in the frame of the measure 15.2 "support to the conservation and use of forest genetic resources" and under Regulation (EU) No 1305/2013 of the European Parliament and of the Council of 17 December 2013 on support for rural development by the European Agricultural Fund for Rural Development (EAFRD) with 75% co-financing. This study was funded by the European Union Horizon 2020 research and innovation programme under grant agreement No 773383 (B4EST project), and the Ministry of Science (RTI2018-094691-B-C32)

Related Organizations
Keywords

Seed sourcing, Afforestation, Reforestation, Ecologica restoration, Local seeds

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average