Strategies for Climate-Smart Forest Management in Austria

Exploring climate-smart forestry in Mediterranean forests through an innovative composite climate-smart index

In recent years, Climate-Smart Forestry (CSF) has emerged as an innovative approach to sustainable forest management, aiming to enhance forest resilience and to balance the provision of ecosystem services facing climate-related threats. This study introduces for the first time a new composite climate-smart index (ICSF) to assess CSF. The methodological approach comprises the following steps: (i) the selection and evaluation of CSF indicators; (ii) the weighting of these indicators; and (iii) the assessment of CSF for Mediterranean forests in two distinct periods, specifically 2005 and 2015. Eight indicators were selected from a systematic literature review. The Analytic Hierarchy Process was applied to translate the preferences obtained through an online questionnaire from a network of CSF-expert stakeholders into weights, at both indicators and criteria levels (i.e., adaptation, mitigation, and the social dimension). Results reveals that indicators "tree species composition", "forest damage", and "regeneration" are of crucial importance for CSF assessment. The comparison of the CSF value between the years 2005 and 2015, shows a slight increase in CSF ratings. The ICSF serves as a comprehensive index of CSF covering all aspects of that concept, i.e. adaptation, mitigation, and the social dimension (including production). The national-scale analysis provides an overview of the dynamics that involve forest management of Mediterranean forests against climate change. The study offers a practicable method for CSF evaluation with its allover set of indicators, representing a suitable tool for supporting forest managers to mitigate the negative impacts of climate change.

Past and future impacts of land-use changes on ecosystem services in Austria

Environmental and socio-economic developments induce land-use changes with potentially negative impacts on human well-being. To counteract undesired developments, a profound understanding of the complex relationships between drivers, land use, and ecosystem services is needed. Yet, national studies examining extended time periods are still rare. Based on the Special Report on land use, land management and climate change by the Austrian Panel on Climate Change (APCC), we use the Driver-Pressure-State-Impact-Response (DPSIR) framework to (1) identify the main drivers of land-use change, (2) describe past and future land-use changes in Austria between 1950 and 2100, (3) report related impacts on ecosystem services, and (4) discuss management responses. Our findings indicate that socio-economic drivers (e.g., economic growth, political systems, and technological developments) have influenced past land-use changes the most. The intensification of agricultural land use and urban sprawl have primarily led to declining ecosystem services in the lowlands. In mountain regions, the abandonment of mountain grassland has prompted a shift from provisioning to regulating services. However, simulations indicate that accelerating climate change will surpass socio-economic drivers in significance towards the end of this century, particularly in intensively used agricultural areas. Although climate change-induced impacts on ecosystem services remain uncertain, it can be expected that the range of land-use management options will be restricted in the future. Consequently, policymaking should prioritize the development of integrated land-use planning to safeguard ecosystem services, accounting for future environmental and socio-economic uncertainties.

Effects of Silvicultural Adaptation Measures on Carbon Stock of Austrian Forests

We present the results of a simulation experiment that evaluated three scenarios of forest management in the context of climate change mitigation. Two scenarios refer to climate change adaptation measures. The third scenario was a business-as-usual scenario representing the continuation of current forest management. We wanted to know whether a change in tree species composition or the implementation of shorter rotation cycles is in accordance with the objectives of climate change mitigation. Our simulation experiment was based on data of the Austrian National Forest Inventory. A forest sector simulation model was used to derive timber demand and potential harvesting rates. Forest dynamics were simulated with an individual-tree growth model. We compared carbon stocks, harvesting rates, current annual increment, salvage logging, and forest structure. Compared to the business-as-usual scenario, a change in tree species composition and shorter rotation cycles reduce salvage logging by 14% and 32%, respectively. However, shorter rotation cycles reduce the carbon stock by 27%, but increase the harvesting rate by 4.8% within the simulation period of 140 years. For changes in the tree species composition, the results were the opposite. Here, the carbon stock is increased by 47%, but the harvesting rate is reduced by 15%. Thus, there are clear tradeoffs between the different ecosystem services depending on the climate change adaptation scenario. We also show that a fundamental change in forest management must be accompanied by a transformation in wood processing technology and innovation in wood utilization.

Bringing “Climate-Smart Forestry” Down to the Local Level—Identifying Barriers, Pathways and Indicators for Its Implementation in Practice

The theoretical concept of “climate-smart forestry” aims to integrate climate change mitigation and adaptation to maintain and enhance forests’ contributions to people and global agendas. We carried out two local transdisciplinary collaboration processes with the aim of developing local articulations of climate-smart forestry and to identify barriers, pathways and indicators to applying it in practice. During workshops in northern and southern Sweden, local stakeholders described how they would like forests to be managed, considering their past experiences, future visions and climate change. As a result, the stakeholders framed climate-smart forestry as active and diverse management towards multiple goals. They identified several conditions that could act both as barriers and pathways for its implementation in practice, such as value chains for forest products and services, local knowledge and experiences of different management alternatives, and the management of ungulates. Based on the workshop material, a total of 39 indicators for climate-smart forestry were identified, of which six were novel indicators adding to the existing literature. Our results emphasize the importance of understanding the local perspectives to promote climate-smart forestry practices across Europe. We also suggest how the concept of climate-smart forestry can be further developed, through the interplay between theory and practice.

Allometry and Post-Drought Growth Resilience of Pedunculate Oak (Quercus robur L.) Varieties

This paper presents an analysis of the radial growth, tree dimensions, and allometry of three phenological pedunculate oak (Quercus robur L.; QURO) varieties (early (E-QURO), typical (T-QURO), and late (L-QURO)), from a common garden experiment. We focused on the resistance and resilience of each variety to drought events, which occurred in 2012 and 2017, as well as their recovery potential during juvenile and mature growth phases, with the goal of clarifying how QURO drought sensitivity is influenced by tree phenology and growth stage. Our results indicate that E-QURO is more drought resistant, while T-QURO and L-QURO exhibit greater recovery potential after a drought event. Hence, typical and late QURO varieties are better prepared to withstand climate change. We also noted differences in the physical dimensions and the allometry of the studied QURO varieties. On average, 21-year-old QURO specimens from the analyzed stand are 9.35 m tall, have a crown width (CW) of 8.05 m, and a diameter at breast height (DBH) of 23.71 cm. Although T-QURO varieties had the greatest DBH and CW, they were shorter than E- and L-QURO, which are similar in height. T-QURO is also shorter relative to DBH, while L-QURO has a wider crown relative to tree height (TH). Intra-variety variations are higher than variations among half-sib (open-pollinated) families of each variety. Moreover, the adopted regression model provided a better fit to the CW/DBH ratio than to TH/DBH and CW/TH.

Silvicultural Interventions Drive the Changes in Soil Organic Carbon in Romanian Forests According to Two Model Simulations

We investigated the effects of forest management on the carbon (C) dynamics in Romanian forest soils, using two model simulations: CBM-CFS3 and Yasso15. Default parametrization of the models and harmonized litterfall simulated by CBM provided satisfactory results when compared to observed data from National Forest Inventory (NFI). We explored a stratification approach to investigate the improvement of soil C prediction. For stratification on forest types only, the NRMSE (i.e., normalized RMSE of simulated vs. NFI) was approximately 26%, for both models; the NRMSE values reduced to 13% when stratification was done based on climate only. Assuming the continuation of the current forest management practices for a period of 50 years, both models simulated a very small C sink during simulation period (0.05 MgC ha−1 yr−1). Yet, a change towards extensive forest management practices would yield a constant, minor accumulation of soil C, while more intensive practices would yield a constant, minor loss of soil C. For the maximum wood supply scenario (entire volume increment is removed by silvicultural interventions during the simulated period) Yasso15 resulted in larger emissions (−0.3 MgC ha−1 yr−1) than CBM (−0.1 MgC ha−1 yr−1). Under ‘no interventions’ scenario, both models simulated a stable accumulation of C which was, nevertheless, larger in Yasso15 (0.35 MgC ha−1 yr−1) compared to CBM-CSF (0.18 MgC ha−1 yr−1). The simulation of C stock change showed a strong “start-up” effect during the first decade of the simulation, for both models, explained by the difference in litterfall applied to each scenario compared to the spinoff scenario. Stratification at regional scale based on climate and forest types, represented a reasonable spatial stratification, that improved the prediction of soil C stock and stock change.

Root Reinforcement in Slope Stability Models: A Review

The influence of vegetation on mechanical and hydrological soil behavior represents a significant factor to be considered in shallow landslides modelling. Among the multiple effects exerted by vegetation, root reinforcement is widely recognized as one of the most relevant for slope stability. Lately, the literature has been greatly enriched by novel research on this phenomenon. To investigate which aspects have been most treated, which results have been obtained and which aspects require further attention, we reviewed papers published during the period of 2015–2020 dealing with root reinforcement. This paper—after introducing main effects of vegetation on slope stability, recalling studies of reference—provides a synthesis of the main contributions to the subtopics: (i) approaches for estimating root reinforcement distribution at a regional scale; (ii) new slope stability models, including root reinforcement and (iii) the influence of particular plant species, forest management, forest structure, wildfires and soil moisture gradient on root reinforcement. Including root reinforcement in slope stability analysis has resulted a topic receiving growing attention, particularly in Europe; in addition, research interests are also emerging in Asia. Despite recent advances, including root reinforcement into regional models still represents a research challenge, because of its high spatial and temporal variability: only a few applications are reported about areas of hundreds of square kilometers. The most promising and necessary future research directions include the study of soil moisture gradient and wildfire controls on the root strength, as these aspects have not been fully integrated into slope stability modelling.