Climate change

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

Economic performance of uneven-aged forests analysed with annuities

For this study, 18 permanent research plots in Switzerland with an area between 0.5 and 2.5 ha that have been installed between 1905 and 1931 were analysed using annuities. The plots cover a wide range of uneven-aged forest-types from pure Norway spruce to classical single-tree selection (plenter) forests dominated by Silver fir in different elevations (575-1810 m a.s.l). The areas have been managed according to an uneven-aged silvicultural system and growth and yield characteristics have been assessed on a single-tree basis every 5-11 years. Net revenues of timber harvesting were computed as a time series from the installation of the plots until today and transformed into net present values and subsequently into annuities for each assessment interval. Three types of annuities: (1) for cutting cycles; (2) forward; (3) backward for the whole assessment period were calculated together with internal rates of return. The results display that annuities were usually positive with an interest of 2 per cent. High elevation (>1400 m) Norway spruce dominated forests as well as heavily overstocked (>900-1000 m3 ha−1) plots showed the lowest or even negative annuities. The reduction of overstocks lead in the mid-term to an increase, but resulted in a short-term decrease of the annuities. For many of the research plots, especially those in higher elevations, there is a trend towards an increase of the annuities over time. The highest annuities were found in Silver fir dominated selection forests with a growing stock close to or slightly above an equilibrium structure. The backward calculation of the annuities improved for some plots the problem of the strong influence of the value of the initial growing stock. Implications for uneven-aged silviculture as well as for the analysis of the economic performance of uneven-aged and even-aged forests and the application of annuities are discussed in the pape

Machine learning based soil maps for a wide range of soil properties for the forested area of Switzerland

Spatial soil information in forests is crucial to assess ecosystem services such as carbon storage, water purification or biodiversity. However, spatially continuous information on soil properties at adequate resolution is rare in forested areas, especially in mountain regions. Therefore, we aimed to build high-resolution soil property maps for pH, soil organic carbon, clay, sand, gravel and soil density for six depth intervals as well as for soil thickness for the entire forested area of Switzerland. We used legacy data from 2071 soil profiles and evaluated six different modelling approaches of digital soil mapping, namely lasso, robust external-drift kriging, geoadditive modelling, quantile regression forest (QRF), cubist and support vector machines. Moreover, we combined the predictions of the individual models by applying a weighted model averaging approach. All models were built from a large set of potential covariates which included e.g. multi-scale terrain attributes and remote sensing data characterizing vegetation cover. Model performances, evaluated against an independent dataset were similar for all methods. However, QRF achieved the best prediction performance in most cases (18 out of 37 models), while model averaging outperformed the individual models in five cases. For the final soil property maps we therefore used the QRF predictions. Prediction performance showed large differences for the individual soil properties. While for fine earth density the R2 of QRF varied between 0.51 and 0.64 across all depth intervals, soil organic carbon content was more difficult to predict (R2 = 0.19–0.32). Since QRF was used for map prediction, we assessed the 90% prediction intervals from which we derived uncertainty maps. The latter are valuable to better interpret the predictions and provide guidance for future mapping campaigns to improve the soil maps

Vulnerability of uneven-aged forests to storm damage

Uneven-aged forests are assumed to have a high stability against storm damage but have rarely been analysed for vulnerability to storm damage due to a lack of a sufficient empirical database. Here we model storm damage in uneven-aged forest to analyse major factors that may determine the sensitivity of this type of forests to storms based on a broad database. Data are derived of public forests in the canton Neuchâtel in West Switzerland that are dominated by silver fir and Norway spruce and managed since the beginning of the 20th century following a single-tree selection system. A unique dataset of periodical (every 5-10 years) full inventories measuring the diameter of every single tree including salvage cuttings was available for the investigation. The time series reached back until 1920 and covered an area of 16 000 ha divided into 3000 divisions. The effect of a major winter storm (‘Lothar') in December 1999 on these forests was investigated using a subset of 648 divisions. The influence of the vertical stand structure on the vulnerability of storm damage was studied using logistic regression models. To facilitate the analyses, an index of closeness to a J-shaped distribution (LikeJ) based on the number of trees in different diameter classes was developed. Besides structural indices, variables representing stand characteristics, soil-related and topography-related variables were included. The results of our study show that the overall damage level of the investigated forests was rather low. The variables that entered the model for the uneven-aged stands were different to those that are normally significant for even-aged stands. While variables like stand structure, the timing of the harvesting and topographic variables entered a multivariate statistical model as significant predictors, standard predictors for storm damage in even-aged stands such as stand density, thinning intensity or species composition were not significant. We hypothesize that the uneven-aged structure of the investigated forests may be one reason for the low damage level we observed but emphasize the need for more detailed research to support this conclusio

Enfoques recientes para modelizar el riesgo de tormentas y fuego en los bosques europeos y su integración

The aim of this paper is to discuss the different recently developed empirical and mechanistic modelling approaches for assessing the risk of wind and fire damage to forests. Additionally the work will explore possible ways to integrate these approaches, including feedback mechanisms, into growth and yield models and decision support tools used in forestry. The integration of mechanistic and empirical storm risk models, as well as an empirical/mechanistic fire risk model into growth simulators is demonstrated and future challenges and options for risk modelling and for creating complex decision support tools, including growth simulators, meteorological components and risk modules, are discussed.El objetivo de este trabajo es analizar los diferentes modelos empíricos y mecanicistas que se han desarrollado recientemente para evaluar el riesgo de daños por el viento y el fuego en los bosques. Además, el trabajo explora las posibles formas de integrar estos enfoques, incluyendo mecanismos de retroalimentación, en los modelos de crecimiento y produccion y en las herramientas de apoyo a la toma de decisiones utilizadas en el sector forestal. Se muestra la integración de modelos mecanicistas y empíricos de riesgo a tormentas, así como un modelo empírico/mecanicista de riesgo de incendio en los simuladores de crecimiento y se discuten los retos futuros y las opciones para la modelización de riesgos y para la creación de complejas herramientas de apoyo a la toma de decisiones, incluyendo simuladores de crecimiento, componentes meteorológicos y módulos de riesgo

Forest owner motivations and attitudes towards supplying biomass for energy in Europe

The European Commission expects the use of biomass for energy in the EU to increase significantly between 2010 and 2020 to meet a legally binding target to cover at least 20% of EU’s total energy use from renewable sources in 2020. According to estimates made by the member states of the EU, the direct supply of biomass from forests is expected to increase by 45% on a volume basis between 2006 and 2020 in response to increasing demand (Beurskens LWM, Hekkenberg M, Vethman P. Renewable energy projections as published in the national renewable energy action plans of the European Member states. ECN and EEA; 2011. http://https://www.ecn.nl/docs/library/report/2010/e10069.pdf [accessed 25.04.2014]; Dees M, Yousef A, Ermert J. Analysis of the quantitative tables of the national renewable energy action plans prepared by the 27 European Union Member States in 2010. BEE working paper D7.2. Biomass Energy Europe project. FELIS e Department of Remote Sensing and landscape information Systems, University of Freiburg, Germany; 2011). Our aims were to test the hypotheses that European private forest owners’ attitudes towards supplying woody biomass for energy (1) can be explained by their responses to changes in prices and markets and (2) are positive so that the forest biomass share of the EU 2020 renewable energy target can be met. Based on survey data collected in 2010 from 800 private forest owners in Sweden, Germany and Portugal our results show that the respondents’ attitudes towards supplying woody biomass for energy cannot be explained as direct responses to changes in prices and markets. Our results, furthermore, imply that European private forest owners cannot be expected to supply the requested amounts of woody biomass for energy to meet the forest biomass share of the EU 2020 renewable energy target, at least if stemwood is to play the important role as studies by Verkerk PJ, Anttila P, Eggers J, Lindner M, Asikainen A. The realisable potential supply of woody biomass fromforests in the European Union. For Ecol Manag 2011;261: 2007e2015, UNECE and FAO. The European forest sector outlook study IIinfo:eu-repo/semantics/publishedVersio

Forest Owners' Response to Climate Change : University Education Trumps Value Profile

Do forest owners’ levels of education or value profiles explain their responses to climate change? The cultural cognition thesis (CCT) has cast serious doubt on the familiar and often criticized "knowledge deficit" model, which says that laypeople are less concerned about climate change because they lack scientific knowledge. Advocates of CCT maintain that citizens with the highest degrees of scientific literacy and numeracy are not the most concerned about climate change. Rather, this is the group in which cultural polarization is greatest, and thus individuals with more limited scientific literacy and numeracy are more concerned about climate change under certain circumstances than those with higher scientific literacy and numeracy. The CCT predicts that cultural and other values will trump the positive effects of education on some forest owners' attitudes to climate change. Here, using survey data collected in 2010 from 766 private forest owners in Sweden and Germany, we provide the first evidence that perceptions of climate change risk are uncorrelated with, or sometimes positively correlated with, education level and can be explained without reference to cultural or other values. We conclude that the recent claim that advanced scientific literacy and numeracy polarizes perceptions of climate change risk is unsupported by the forest owner data. In neither of the two countries was university education found to reduce the perception of risk from climate change. Indeed in most cases university education increased the perception of risk. Even more importantly, the effect of university education was not dependent on the individuals' value profile