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Although native to Australia, Eucalyptus species are found throughout Europe. At present, they are located mainly in the Iberian Peninsula and Eucalyptus globulus is the most commonly planted species. Climate forecasts anticipate an expansion of Eucalyptus to other regions of Europe. The fast growth of E. globulus, together with its resprouting ability and wood properties, has promoted the use of this species in the Iberian Peninsula. The total volume of E. globulus harvested there was close to 14 million m3 in 2019. Eucalyptus species represent the main source of raw material for the pulp and paper industries and provide an important source of income to non-industrial owners. Being exotic fast-growing trees, their expansion has also been associated with negative environmental impacts. The species therefore poses a series of challenges, while also generating opportunities. The objectives of this review paper are: (1) to summarize the importance of Eucalyptus plantations in Europe; (2) to analyse the opportunities and challenges of this genus in present and future plantations in Europe; (3) to assess to what extent forest management, at both stand and landscape levels, can reduce negative impacts; (4) to make policy and management recommendations that may support the use of this genus in other European regions. These aims are accomplished based on a thorough literature review, particularly focused on research developed in the Iberian Peninsula. [ABSTRACT FROM AUTHOR]

Abstract: Criteria and indicators (C & I) to evaluate the sustainability of forest management have been proposed by the Ministerial Conference on the Protection of Forests in Europe. Although primarily defined at the national scale, these C & I also have implications at scales ranging from forest stands to the forest management unit. In this paper, we review existing forest growth and ecosystem models from the point of view of applicability to prediction of indicators of sustainable management, focusing on stand scale models and management. To do this, we first present a conceptual framework for understanding the role of models in assessing forest management at the stand level in the context of sustainability criteria and indicators. We classify the criteria into those predictable using models operating at the stand scale, and those derivable either through scaling up or as solutions of a multi-objective management optimisation problem. We conclude that to date, no comprehensive models exist that could be used to predict all the indicators simultaneously. The most promising approach seems to be a modular system where different models are combined and run simultaneously, with shared inputs and well defined mutual links. More modelling efforts are needed especially regarding the state of the soil, including carbon, nitrogen and water balances and physical effects. Models also need development in their ability to deal with heterogeneous stand structures and with non-woody forest products such as berries, mushrooms or cork. The outputs of the models need to be developed in a direction where they can be interpreted in terms of the recreational or biodiversity value of the forest. Data requirements are most pronounced on the same issues as the gaps in model availability. It would be important to consider amending the national forest inventories and other similar standard data collection protocols with variables required for sustainability assessment. Importantly, combining different models in a modular system and with variable data sources requires advanced model parameterisation and evaluation methods and assessment of parameter and model uncertainty. The probabilistic, Bayesian approaches hold a lot of promise in this respect. Predictions using several different models or model systems, with systematic analysis of e.g. inter-model variability, could also be considered. [Copyright &y& Elsevier]

Knowledge of factors that trigger human response to climate change is crucial for effective climate change policy communication. Climate change has been claimed to have low salience as a risk issue because it cannot be directly experienced. Still, personal factors such as strength of belief in local effects of climate change have been shown to correlate strongly with responses to climate change and there is a growing literature on the hypothesis that personal experience of climate change (and/or its effects) explains responses to climate change. Here we provide, using survey data from 845 private forest owners operating in a wide range of bio-climatic as well as economic-social-political structures in a latitudinal gradient across Europe, the first evidence that the personal strength of belief and perception of local effects of climate change, highly significantly explain human responses to climate change. A logistic regression model was fitted to the two variables, estimating expected probabilities ranging from 0.07 (SD ± 0.01) to 0.81 (SD ± 0.03) for self-reported adaptive measures taken. Adding socio-demographic variables improved the fit, estimating expected probabilities ranging from 0.022 (SD ± 0.008) to 0.91 (SD ± 0.02). We conclude that to explain and predict adaptation to climate change, the combination of personal experience and belief must be considered.