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An integral understanding of forest biodiversity requires the exploration of the many aspects it comprises and of the numerous potential determinants of their distribution. The landscape ecological approach provides a necessary complement to conventional local studies that focus on individual plots or forest ownerships. However, most previous landscape studies used equally-sized cells as units of analysis to identify the factors affecting forest biodiversity distribution. Stratification of the analysis by habitats with a relatively homogeneous forest composition might be more adequate to capture the underlying patterns associated to the formation and development of a particular ensemble of interacting forest species. Here we used a landscape perspective in order to improve our understanding on the influence of large-scale explanatory factors on forest biodiversity indicators in Spanish habitats, covering a wide latitudinal and altitudinal range. We considered six forest biodiversity indicators estimated from more than 30,000 field plots in the Spanish national forest inventory, distributed in 213 forest habitats over 16 Spanish provinces. We explored biodiversity response to various environmental (climate and topography) and landscape configuration (fragmentation and shape complexity) variables through multiple linear regression models (built and assessed through the Akaike Information Criterion). In particular, we took into account the inherent model uncertainty when dealing with a complex and large set of variables, and considered different plausible models and their probability of being the best candidate for the observed data. Our results showed that compositional indicators (species richness and diversity) were mostly explained by environmental factors. Models for structural indicators (standing deadwood and stand complexity) had the worst fits and selection uncertainties, but did show significant associations with some configuration metrics. In general, biodiversity increased in habitats covering wider topographic ranges and comprising forest patches with more complex shapes. Patterns in other relationships varied between indicators (e.g. species richness vs. diversity), or even were opposed (trees vs. shrubs). Our study (1) allowed deepening the understanding of biodiversity patterns in a large set of Spanish forest habitats and (2) highlighted the increasing complexity of identifying common landscape conditions favouring forest biodiversity as the range of analysed biodiversity aspects is widened beyond the more commonly assessed species richness indicators., El estudio integral de la biodiversidad requiere la exploración de sus numerosos componentes y de los diversos factores potencialmente determinantes de su distribución. El enfoque de la ecología y escala de paisaje representa un complemento necesario a los estudios locales centrados en parcelas de inventario o montes individuales. No obstante, la mayoría de los estudios a escala de paisaje han utilizado cuadrículas como unidad de análisis para la identificación de los factores responsables de la distribución de la biodiversidad. La estratificación del territorio por hábitats forestales con una composición relativamente más homogénea podría ser más adecuada de cara a la identificación de los patrones subyacentes asociados a la formación y desarrollo de un determinado conjunto de especies forestales relacionadas funcionalmente. En este estudio adoptamos una perspectiva de paisaje para profundizar en el conocimiento de la influencia de factores a grandes escalas espaciales sobre la biodiversidad forestal de los hábitats forestales españoles, cubriendo un amplio rango latitudinal y altitudinal. Consideramos seis indicadores de biodiversidad forestal estimados a partir de más de 30.000 parcelas del inventario forestal nacional de España, distribuidas en 213 hábitats forestales y 16 provincias diferentes. Exploramos la respuesta de la biodiversidad frente a diversas variables ambientales (clima y topografía) y de configuración del paisaje (fragmentación y complejidad de formas), a través de modelos de regresión lineal múltiple (creados y evaluados con el Criterio de Información de Akaike). En concreto, tenemos en cuenta la incertidumbre inherente a la selección del mejor modelo al analizar conjuntos de datos complejos, y consideramos diferentes modelos posibles y su probabilidad de ser considerados como el mejor candidato para explicar la variabilidad observada. Nuestros resultados mostraron que los indicadores de composición (riqueza y diversidad de especies) fueron principalmente explicados por los factores ambientales. Los modelos para los indicadores estructurales (madera muerta en pie y complejidad del rodal) tuvieron los peores ajustes e incertidumbres de selección, pero mostraron una asociación significativa con algunos de los índices de configuración. En general, la biodiversidad aumentó en los hábitats que abarcan un mayor rango altitudinal y con teselas de formas más complejas. El resto de patrones en las relaciones variaron entre indicadores (e.g. riqueza vs. diversidad de especies), o incluso presentaron tendencias opuestas (árboles vs. arbustos). Nuestro estudio permite profundizar en la comprensión de los patrones de biodiversidad a través de un amplio conjunto de hábitats forestales españoles y pone de manifiesto la creciente complejidad y dificultad de identificar un conjunto común de condiciones del paisaje que favorezcan la biodiversidad forestal a medida que se amplía el número de aspectos analizados más allá de los más habitualmente considerados indicadores de riqueza de especies.

Centro de Investigación Forestal (CIFOR), The increasing demand for innovative forest management strategies to adapt to and mitigate climate change and benefit forest production, the so-called Climate-Smart Forestry, calls for a tool to monitor and evaluate their implementation and their effects on forest development over time. The pan-European set of criteria and indicators for sustainable forest management is considered one of the most important tools for assessing many aspects of forest management and sustainability. This study offers an analytical approach to selecting a subset of indicators to support the implementation of Climate-Smart Forestry. Based on a literature review and the analytical hierarchical approach, 10 indicators were selected to assess, in particular, mitigation and adaptation. These indicators were used to assess the state of the Climate-Smart Forestry trend in Europe from 1990 to 2015 using data from the reports on the State of Europe’s Forests. Forest damage, tree species composition, and carbon stock were the most important indicators. Though the trend was overall positive with regard to adaptation and mitigation, its evaluation was partly hindered by the lack of data. We advocate for increased efforts to harmonize international reporting and for further integrating the goals of Climate-Smart Forestry into national-and European-level forest policy making., This study generated from the COST (European Cooperation in Science and Technology) Action CLIMO (Climate-Smart Forestry in Mountain Regions — CA15226) was financially supported by the EU Framework Programme for Research and Innovation HORIZON 2020. Most of the work was carried out during the Short Term Scientific Mission that Giovanni Santopuoli undertook at the WSL in Birmensdorf (Switzerland) hosted by Christian Temperli, Alessandra Bottero, Paolo Cherubini, and Marco Ferretti., 10 Pág.

Unimodal response of tree species richness to increases in aboveground productivity is evident in grasslands butto a lesser extent in forests, where confounding factors (e.g., abiotic factors and management regimes) may alterthe response and compromise the delivery of ecosystem services. We hypothesize that unimodalresponse of bio-mass accumulation through increased species richness leads to greater tree above ground carbon (AGC) stocksand thus climate regulation but not necessarily higher timber volume production for human consumption acrossportions of North American and European forests. Wefirst evaluated the biodiversity-productivity pattern andassessed if the addition of potential confounding variables altered the response. Afterwards, we integrated directand indirect effects of species richness and confounding factors in the modelling of aboveground carbon stockand timber volume. We confirm an increase in carbon stocks concomitant with an increase in tree species rich-ness up to an optimum biomass value in both regions. Tree species richness had a marginal effect on both above-groundcarbonstocks and timber volumewitha trade-offinthe easternUS. Biomassaccumulation islower intreeplantations than in natural forests, although volume increased with species richness. Naturally-regenerated for-ests needed as much as double the number of tree species than plantations to reach the same carbon stocks. Dis-tinct ecosystem services (AGC and timber volume) showed unique pathways of achieving their maximumprovisioning. As increasing forest resilience to global change requires a fundamental understanding of howtree species combine with changing climatic conditions to drive the provisioning of various ecosystem services,further examination of this study'sfindings across additional biogeographical regions may lead the way tounraveling such dynamics and empowering adaptive management., We acknowledge support of the publication fee by the CSIC Open Access Publication Support Initiative through its Unit of Information Resources for Research (URICI).