Under increasing human-related threats to forests, many studies suggest that increasing tree species diversity may boost forest resilience by enhancing the range of species’ responses to disturbances. However, it remains unclear whether passive or active forest management strategies should be applied to increase tree diversity. This issue would benefit from investigating which management and environmental factors, together with species’ functional traits influence temporal changes in tree species diversity.

We explored the influence of the bioclimatic region, land-use history, forest cover, protection, management, forest structure and changes in temperature and precipitation, to explain tree species diversity changes in NE Iberian forests, by comparing 3141 plots from the Spanish National Forest Inventory sampled between 1989 and 2016. Moreover, we assessed which species’ functional traits (dispersal habit, drought and shade tolerance) were most relevant for diversity changes.

After 27 years, tree species richness and diversity moderately increased in the tree and regeneration layers. This trend occurred mostly in long-established, non-recently managed forests and in those with a lower initial basal area. Increasing temperature had negative effects for diversity increase in the tree layer but positive for the regeneration compartment, while decreasing precipitation showed the opposite effects.

Tree species with higher drought tolerance, and especially those animal-dispersed ones arriving from the regional pool, mostly contributed to the local diversity increase. This pattern occurred in all forest types, although the taxonomic array of species varied.

Synthesis and applications: The main drivers influencing the passive increase in tree species diversity suggest a primary role of diminishing forest exploitation in this recovery process, fine-tuned by climatic changes. This ecological scenario has particularly favored animal-dispersed tree species with higher drought tolerance, which mostly led the diversity increase. A higher presence of such highly mobile and drought-tolerant species can be crucial to increase functional diversity and, ultimately, increase forest resilience under future scenarios of greater aridity. In light of these results, management strategies should continue fostering the restoration of diversity in once intensively exploited forests while ensuring the maintenance of the already gained tree species diversity.

Forest inventory data: Data of 3141 replicated plots from the second (NFI2) and fourth (NFI4) Spanish National Forest Inventories for Catalonia was used. The NFI2 took place during 1989–1990 (hereafter 1989), while the IFN4 was conducted during 2013-2016 (hereafter 2016). Data on species composition and abundance of the tree (individuals ≥7.5 cm in dbh) and regeneration (individuals < 7.5 cm in dbh) layers was extracted. Detailed information on experimental design is available in our paper which will be published in the Journal of Applied Ecology. 

Diversity change: For each plot and inventory, we calculated diversity metrics using Hill numbers of order q=0 (i.e., transformation of species richness), q=1 (i.e., transformation of the Shannon diversity index), q=2 (i.e., transformation of the Simpson diversity index), and the Pielou’s Evenness Index. Then, we calculated the absolute change for each diversity metric between NFI2 and NFI4 for the tree and regeneration layers. 

Factors influencing diversity changes: 

• Bioclimatic region: each plot was classified according to the Bioclimatic Classification for Continental Spain, defined by the thermicity index, resulting in three broad bioclimatic regions: (1) mesomediterranean, (2) supramediterranean, and (3) montane. 

• Land use history and forest cover: each plot was classified into two types of land-use history trajectories: (1) “long existing forests” as those that were already present in 1956, and (2) “recent forests” as those that were located in pasturelands and croplands in 1956 and established after rural abandonment. The proportion of forest cover surrounding each NFI plot was calculated to account for forest connectivity in the landscape. For such, we used land cover maps derived from Landsat imagery corresponding to the years 1987 and 2017, which reasonably matched our study period (1989-2016)

• Forest protection: we identified those plots included in the Catalan system of protected areas.

• Past and recent forest management: management prior to the NFI2 was obtained from evidence observed and recorded during the NFI2 field survey in 1989–1990, while recent management between 1986 and 2016 was obtained from the disturbance map developed by Senf & Seidl (2021) using satellite data and manually interpreted plots.

• Forest structure: total basal area (m² ha^-1) of the NFI2 plots was obtained as a measure of the initial forest structure.

• Temperature and precipitation changes: we used aggregated data of the years 1988–1992 as representative of the NFI2 period, and the years 2011–2015 as to characterize the NFI4 period, obtained from the Climate Engine database at 9.6 km daily resolution (AgERA5).

Functional trait data: All species were clustered according to seed dispersal type: animal-dispersed (dispersed by birds and mammals) vs. other dispersal methods, and to shade and drought tolerance. Clustering resulted in four distinct groups of species, distinguishing: (C1) animal-dispersed species with lower drought and higher shade tolerance (e.g., Fagus sylvatica, Prunus avium, Ilex aquifolium), (C2) animal-dispersed with higher drought and lower shade tolerance (e.g., Crataegus monogyna, Arbutus unedo, Quercus spp.), (C3) species with other dispersal methods with lower drought and higher shade tolerance (e.g., Abies alba, Fraxinus excelsior, Acer campestre), and (C4) species with other dispersal methods and higher drought and lower shade tolerance (e.g., P. nigra, P. halepensis, Acer monspesulanum).

Provenance of new recruited species: By comparing both NFIs we identified those plots that gained species during the study period and we built a new metric based on the presence/absence information of each species in each plot and NFI period. This metric allowed us to address whether a new species that appeared in the tree or the regeneration layer in NFI4 inventory was already present in the NFI2 and thus recruited from inside the plot (therefore local pool); or the new recruited species was not present in the NFI2 plots and arrived from outside the plot (therefore regional pool).

Please note that all detailed information on data acquisition and experimental design is available in our paper which is published in the Journal of Applied Ecology.