Climate change is producing threats to forests’ capacity of regulating water regimes. Therefore, thinning strategies can be applied to mitigate climate change impacts more efficiently by providing more spaces for trees to utilize resources e.g., water and nutrients. This study examined the effects of different thinning intensities and intervals on water characteristics and biomass growth of a 75-year-old Norway spruce (Picea abies) stand in the Black Forest, Germany. Here we used a water and management sensitive update of the process-based forest growth model 3PG, 3PG-Hydro. We applied light (10%), moderate (30%), and heavy thinning (50% intensity) in the interval of 10, 25, and 50 years of the management period. We simulated growth with climate change scenario RCP 8.5 data from 1995 to 2065. We analyzed the effects of the different thinning regimens on biomass, evapotranspiration as well as water yield. Thinning intensity and interval as well as their interaction have significant influence on production of stand biomass and water yield for all thinning regimes applied (p < 0.05). However, there is no significant difference (p > 0.05) in accumulated biomass (thinned biomass added to the stand biomass) between the applied thinning regimes. Light thinning in a long interval (50 years) produced highest stand biomass among the applied thinning regimes. Furthermore, the prediction showed that accumulated water yield increased with increasing thinning intensity. Our study concludes that repeated moderate thinning at intermediate intervals results in a high water yield without losing biomass production.

Forest growth function and water cycle are affected by climatic conditions, making climate-sensitive models, e.g., process-based, crucial to the simulation of dynamics of forest and water interactions. A rewarded and widely applied model for forest growth analysis and management, 3PG, is a physiological process-based forest stand model that predicts growth. However, the model runs on a monthly basis and uses a simple soil-water module. Therefore, we downscale the temporal resolution to operate daily, improve the growth modifiers and add a responsive hydrological sub-model to represents the key features of a snow routine, a detailed soil-water model and a separated soil-evaporation calculation. Thereby, we aim to more precisely analyze the effects of thinning events on forest productivity and water services. The novel calibrated 3PG-Hydro model was validated in Norway spruce sites in Southern Germany and confirmed improvements in building forest processes (evapotranspiration) and predicting forest growth (biomass, diameter, volume), as well as water processes and services (water recharge). The model is more sensitive to forest management measures and variability in soil water by (1) individualization of each site’s soil, (2) simulation of percolation and runoff processes, (3) separation of transpiration and evapotranspiration to predict good evapotranspiration even if high thinning is applied, (4) calculation in daily time steps to better simulate variation and especially drought and (5) an improved soil-water modifier. The new 3PG-Hydro model can, in general, better simulate forest growth (stand volume, average diameter), as well as details of soil and water processes after thinning events. The novel developments add complexity to the model, but the additions are crucial and relevant, and the model remains an easy-to-handle forest simulation tool.

Forests are increasingly affected by climate change, highlighting the necessity of adaptive management to sustain ecosystem services. Yet adaptation is complicated by the interplay between ecological and socioeconomic considerations. We used an informed questionnaire to survey a selected group of forest professionals across different European sites, focusing on how perceptions of climate and socioeconomic change drive adaptive management choices. Here we show that professionals broadly agree on the negative impacts of climate change, with drought emerging as the dominant high-risk factor, while perceived socioeconomic change reflects rising timber demand and prices alongside higher operational costs. Professionals rank species diversity, mixing broadleaf and conifer species, and assisted natural regeneration as the priority adaptive measures, yet anticipated timber price increases lead a quarter of respondents to favor maintaining or increasing conifer shares. Economic expectations can change adaptation choices, highlighting a tension between ecological resilience and socioeconomic priorities that forest policy needs to address.

Climate-impact assessments increasingly use high-resolution climate forcing, often assuming that finer spatial detail improves impact projections. Yet this assumption has rarely been tested systematically across impact sectors, regions, and forcing variables. Here we use coordinated simulations from 16 impact models participating in the Inter-Sectoral Impact Model Intercomparison Project to evaluate how increasing forcing resolution from 60 km to 10 km, 3 km, and 1 km affects both climate-input accuracy and impact-model performance. We find that most gains occur when moving from 60 km to 10 km resolution. Further refinement to 3 km and 1 km yields smaller and less consistent benefits, and in some cases degrades performance. Improvements are strongest for temperature-sensitive models and in topographically complex regions, where finer forcing better captures spatial gradients. By contrast, precipitation-driven models and low-relief regions show weaker and less systematic gains. These results challenge the expectation that ever-finer climate forcing necessarily improves impact modelling. Instead, the value of resolution depends on the forcing variable, sector, region, and process representation of the impact model. Benchmarking resolution choices against impact-model performance, rather than climate-input accuracy alone, is therefore essential for designing efficient and decision-relevant climate-impact assessments.