Adaptive forest management (AFM) is an urgent need because of the uncertainty regarding how changes in the climate will affect the structure, composition and function of forests during the next decades. Current research initiatives for the long-term monitoring of impacts of silviculture are scattered and not integrated into research networks, with the consequent losses of opportunities and capacity for action. To increase the scientific and practical impacts of these experiences, it is necessary to establish logical frameworks that harmonize the information and help us to define the most appropriate treatments. In this context, a number of research groups in Spain have produced research achievements and know-how during the last decades that can allow for the improvement in AFM. These groups address the issue of AFM from different fields, such as ecophysiology, ecohydrology and forest ecology, thus resulting in valuable but dispersed expertise. The main objective of this work is to introduce a comprehensive strategy aimed to study the implementation of AFM in Spain. As a first step, a network of 34 experimental sites managed by 14 different research groups is proposed and justified. As a second step, the most important AFM impacts on Mediterranean pines, as one of the most extended natural and planted forest types in Spain, are presented. Finally, open questions dealing with key aspects when attempting to implement an AFM framework are discussed. This study is expected to contribute to better outlining the procedures and steps needed to implement regional frameworks for AFM., A.J. Molina is beneficiary of an “APOSTD” fellowship (APOSTD/2019/111) funded
by the Generalitat Valenciana. M. Moreno-de las Heras is beneficiary of a Serra Hunter fellowship (UB-LE-9055) funded by the Generalitat de Catalunya. F.J. Ruiz-Gómez is supported by a
postdoctoral fellowship of the Junta de Andalucía (Sevilla, Spain), and the European Social Fund
2014–2020 Program (DOC_0055). The authors received national and international funding through
the following projects: SILVADAPT.NET (RED2018-102719-T), ESPECTRAMED (CGL2017-86161-R),
Life-FOREST CO2 (LIFE14 CCM/ES/001271), ALTERACLIM (CGL2015-69773-C2-1-P), INERTIA
(PID2019-111332RB-C22-BDV), CEHYRFO-MED (CGL2017-86839-C3-2-R), DEHESACLIM (IB16185),
RESILIENTFORESTS (LIFE17 CCA/ES/000063), Rhysotto (PID2019-106583RB-I00), AGL2017-83828-
C2-2-R, RTI2018-096884-B-C31, ESPAS (CGL2015-65569-R), and caRRRascal (RTI2018-095037-B-I00).

The assessment of the long-term impacts of drought on tree growth decline using tree-ring analyses may be used to test if plantations are more vulnerable to warming after successive droughts, leading to a “cumulative stress” effect. We selected 76 <i>Pinus pinaster</i> trees (declining and non-declining trees), and basal area increments over the last 20 years (BAI₂₀) were calculated to build the chronologies for the stand types and vigor classes. Resistance, recovery and resilience indices were calculated. Pearson correlations, analyses and Partial Least-Squares regression were used to analyze the relationships among the response and environmental variables. We found a negative and significant relationship between mean temperature for May and June of the current year and growth in the naturally regenerated stands. This negative effect on growth under warm spring conditions was more noticeable in plantations than in naturally regenerated stands. A negative trend along time was found for the resilience index in planted stands. Evapotranspiration, maximum temperature and annual radiation showed significant and negative correlations with the growth of declining trees from planted stands, indicating they are susceptible to drought stress. Declining trees in planted stands showed a loss of growth resilience, specifically a negative trend after successive droughts., This project was funded through the INIA-RTA (RTA2014-00005-00-00) and ESPECTRAMED
(CGL2017-86161-R) projects. We also acknowledge the financial and institutional support of the University of
Cordoba-Campus de Excelencia CEIA3. We thank the “Consejería de Medioambiente y Ordenación del Territorio”
(Junta de Andalucía), the “RED SEDA NETWORK” and “REDIAM” (Junta de Andalucía) for providing field
work and data support. We also thank Javier Cobos for his valuable comments at the beginning of this work, and
Francisco Javier Ruíz Gómez, Rafael Sánchez de la Cuesta, the ERSAF group and, particularly, the staff of the
Dendrochronology, Silviculture and Climate Change Laboratory at Cordoba University, for their assistance during
this research.

Forest ecosystems are increasingly exposed to the combined pressure of climate change and attacks by pests and pathogens. These stress factors can threaten already vulnerable species triggering dieback and rising defoliation and mortality rates. To characterize abiotic (drought, climate warmings) and biotic (pathogens) risks and their spatiotemporal patterns we quantified the recent loss of vitality for the endangered and relict Abies pinsapo forests from Andalusia, south-eastern Spain. Abies pinsapo is an iconic Mediterranean fir showing a high vulnerability to drought stress and also to several pests (Cryphalus numidicus) and root rot fungi (Armillaria mellea). We analyzed a monitoring network dataset of radial growth, defoliation and mortality from 2001 to 2017 including 1025 trees situated in three major mountain ranges (Sierra de Grazalema, Sierra de las Nieves, and Sierra Bermeja). We fitted several statistical models to determine the main drivers of changes in defoliation, a proxy of tree vigor, and mortality. Defoliation and mortality rates were much higher towards the East of the study area, mirroring the gradient from Atlantic to Mediterranean climatic conditions. In the most affected stands tree defoliation increased in response to a combination of long and severe droughts, with attacks by the beetle C. numidicus. Mortality rates increased in response to a higher defoliation rate, a lower relative radial-growth rate, long and severe droughts and a higher incidence of A. mellea. Our findings illustrate the value of monitoring networks recording changes in forest health to quantify and forecast future vulnerability of threatened tree species., The authors thank the Ministerio de Ciencia, Innovación y Universidades (Spain), for providing the necessary financial support for this study through the ESPECTRAMED (CGL2017-86161-R), ISO-PINE (UCO-1265298) and SilvAdapt RED2018 102719 T projects. PGM was supported by a “Juan de la Cierva-Incorporación” contract (MINECO, IJCI-2017-31733) and FJR-G was supported by a post-doctoral fellowship of the Junta de Andalucía (Spain) and the European Social Fund 2014-2020 Program (DOC_0055)., Peer reviewed

Oak trees are declining at an unprecedented rate due to the interaction of many factors, such as pests, diseases, droughts, pollution and flooding. Such abiotic- and biotic-induced stress produces anomalies in plant physiological and functional traits (PTs) that may be spectrally detected, serving to quantify trees’ health status and condition. Previous studies have demonstrated that PTs’ dynamic response can be tracked with hyperspectral and thermal images acquired via aerial platforms. However, the ability to detect the decline at different stages of severity among distinct oak species by using high-resolution multispectral images acquired via miniaturised cameras located aboard unpiloted airborne platforms is still unknown. This cost-effective approach offers improved operability to perform missions with greater continuity and replicability, which is critical to assess the decline progression. In this work, we evaluated the use of airborne multispectral and thermal imagery coupled with a 3-D radiative transfer modelling and machine learning approach for detecting Phytophthora-infected holm oak and cork oak trees. The field study included 2299 trees classified into disease severity classes with a gradient in levels of disease incidence located in Portugal (Ourique and Avis) and Spain (Huelva and Alcuéscar). The classification model achieved an overall accuracy of 76 % (kappa = 0.51) in detecting decline for both species, successfully identifying up to 34 % of declining trees that were not initially detected by visual inspection and confirmed in a reevaluation six months later. When compared against airborne hyperspectral imagery, results yielded comparable accuracy, with a relative decrease of ca. 4 % in overall accuracy and an average Cohen's kappa decrease of 7 %. The results further showed that classification using only hyperspectral imagery is slightly lower but equivalent to using combined multispectral and thermal data, and those derived from these sensors independently are not adequate to classify the different severity stages. The proposed model has enabled us to effectively discern various stages of decline in cork and holm oak forests across diverse geographical areas. Our study, therefore, demonstrates that the tandem use of multispectral and thermal sensors onboard a remotely piloted aircraft platform, together with a radiative transfer modelling and machine learning approach, helps us to predict the impact of this particularly damaging disease on oak trees. This capability facilitates the detection and swift mapping of disease progression, ensuring a proactive approach to forest management., This work was supported by La Caixa Foundation, in partnership with BPI and FCT, in the context of the initiative Promove2020 – O Futuro do Interior. Data collection and processing were partially supported by the QUERCUSAT (CGL2013-40790-R), ESPECTRAMED (CGL2018-86161-R) and D-TRAITS (PID2021-124058OA-I00) projects, part of the Spanish Research Agency, Ministry of Science and Innovation. The study area was selected in collaboration with ACPA project partners. A. Molina and N. Vargas are acknowledged for their support during the RPAS campaign. RHC acknowledges the support received through a fellowship from the Ramon y Cajal Program (RYC2020-029187-I) of the Spanish Ministry of Science, Innovation, and Universities., Peer reviewed