Rebecca S. Snell

Herbaceous Understorey: An Overlooked Player in Forest Landscape Dynamics?

Dense herbaceous understorey layers can impact tree regeneration and thereby affect forest succession. However, the implications of this interaction on large spatial and temporal scales are not well understood. To analyse the role of overstorey–understorey interactions for forest dynamics, we implemented an understorey layer (composed of the plant functional types grasses, forbs, ferns, herbs and shrubs) in the forest landscape model LandClim, focusing on competition for light as the main mode of interaction. The model was used to simulate post-disturbance dynamics over an elevational gradient of 560–2800 m a.s.l. in Central Europe. Simulation results showed strong impacts of the herbaceous understorey on tree regeneration within the first decades, but generally little effect on late-successional forests, i.e. not providing any evidence for ‘arrested’ succession. The results also demonstrated varying overstorey–understorey interactions across the landscape: strongest effects were found at low to mid elevations of the study landscapes, where tree establishment was substantially delayed. At high elevations, tree growth and establishment were more limited by low temperatures, and the effect of light competition from the understorey was negligible. Although the inclusion of large windthrow disturbances increased the biomass of herbaceous understorey across the landscape, this had only a small impact on the overstorey due to the presence of advance regeneration of trees. Overall, our results demonstrate that the herbaceous understorey can have a significant impact for forest landscape dynamics through light competition, and that non-woody plants should not be neglected in forest modelling.

From monocultures to mixed-species forests: is tree diversity key for providing ecosystem services at the landscape scale?

Context Converting monocultures to mixed-species stands is thought to be a promising approach to increase forest productivity and resilience, while additionally providing other ecosystem goods and services (EGS). However, the importance of tree species composition and structure remains unclear, particularly beyond the stand scale due to the difficulty of conducting comprehensive, long-term experiments.ObjectivesTo compare the ability of different tree species mixtures to provide various EGS at the landscape scale.MethodsWe used a dynamic forest landscape model to simulate all possible combinations of dominant tree species for two landscapes; a high-elevation alpine region (Dischma valley, Switzerland) and a lowland valley (Mt. Feldberg, Germany). We evaluated multiple EGS, including protection from gravitational hazards, aboveground biomass, and habitat quality, and examined trade-offs and synergies between them.ResultsMixed-species forests were usually better in providing multiple EGS, although monocultures were often best for single EGS. The simulation results also demonstrated how changing environmental conditions along an elevational gradient had a strong impact on the structure of different species combinations and therefore on the provisioning of EGS.ConclusionTree species diversity alone is not a good predictor of multifunctionality. Mixtures should be selected based on local environmental conditions, complementary functional traits, and the ability to provide the EGS of interest. Although our work focused on current climatic conditions, we discuss how the modelling framework could be employed to consider the impacts of climate change and disturbances to improve our understanding of how mixed-species stands could be used to cope with these challenges.

Overstorey–Understorey Interactions Intensify After Drought-Induced Forest Die-Off: Long-Term Effects for Forest Structure and Composition

Severe drought events increasingly affect forests worldwide, but little is known about their long-term effects at the ecosystem level. Competition between trees and herbs (‘overstorey–understorey competition’) for soil water can reduce tree growth and regeneration success and may thereby alter forest structure and composition. However, these effects are typically ignored in modelling studies. To test the long-term impact of water competition by the herbaceous understorey on forest dynamics, we incorporated this process in the dynamic forest landscape model LandClim. Simulations were performed both with and without understorey under current and future climate scenarios (RCP4.5 and RCP8.5) in a drought-prone inner-Alpine valley in Switzerland. Under current climate, herbaceous understorey reduced tree regeneration biomass by up to 51%, particularly in drought-prone landscape positions (i.e., south-facing, low-elevation slopes), where it also caused a shift in forest composition towards drought-tolerant tree species (for example, Quercus pubescens). For adult trees, the understorey had a minor effect on growth. Under future climate change scenarios, increasing drought frequency and intensity resulted in large-scale mortality of canopy trees, which intensified the competitive interaction between the understorey and tree regeneration. At the driest landscape positions, a complete exclusion of tree regeneration and a shift towards an open, savannah-like vegetation occurred. Overall, our results demonstrate that water competition by the herbaceous understorey can cause long-lasting legacy effects on forest structure and composition across drought-prone landscapes, by affecting the vulnerable recruitment phase. Ignoring herbaceous vegetation may thus lead to a strong underestimation of future drought impacts on forests.

Determining sectoral and regional sensitivity to climate and socio-economic change in Europe using impact response surfaces

Responses to future changes in climatic and socio-economic conditions can be expected to vary between sectors and regions, reflecting differential sensitivity to these highly uncertain factors. A sensitivity analysis was conducted using a suite of impact models (for health, agriculture, biodiversity, land use, floods and forestry) across Europe with respect to changes in key climate and socio-economic variables. Depending on the indicators, aggregated grid or indicative site results are reported for eight rectangular sub-regions that together span Europe from northern Finland to southern Spain and from western Ireland to the Baltic States and eastern Mediterranean, each plotted as scenario-neutral impact response surfaces (IRSs). These depict the modelled behaviour of an impact variable in response to changes in two key explanatory variables. To our knowledge, this is the first time the IRS approach has been applied to changes in socio-economic drivers and over such large regions. The British Isles region showed the smallest sensitivity to both temperature and precipitation, whereas Central Europe showed the strongest responses to temperature and Eastern Europe to precipitation. Across the regions, sensitivity to temperature was lowest for the two indicators of river discharge and highest for Norway spruce productivity. Sensitivity to precipitation was lowest for intensive agricultural land use, maize and potato yields and Scots pine productivity, and highest for Norway spruce productivity. Under future climate projections, North-eastern Europe showed increases in yields of all crops and productivity of all tree species, whereas Central and East Europe showed declines. River discharge indicators and forest productivity (except Holm oak) were projected to decline over southern European regions. Responses were more sensitive to socio-economic than to climate drivers for some impact indicators, as demonstrated for heat-related mortality, coastal flooding and land use.

Importance of climate uncertainty for projections of forest ecosystem services

Mountain forests provide a wide range of ecosystem services (ES, e.g., timber production, protection from natural hazards, maintaining biodiversity) and are especially sensitive to climate change. Dynamic vegetation models are commonly used to project climate change impacts on forests, but the sensitivity of process-based forest landscape models (FLMs) to uncertainties in climate input data has received little attention, especially regarding the response of ES. Using a dry inner-Alpine valley in Switzerland as a case study, we tested the sensitivity of a process-based FLM to different baseline climate data, lapse rates, and future climate change derived from different climate model combination chains and downscaling methods. Under the current climate, different sources of baseline climate accounted for the majority of the variation at lower elevations, while differences in lapse rates caused large variability at higher elevations. Under climate change, differences between climate model chains were the greatest source of uncertainty. In general, the largest differences for species were found at their individual regional distribution limits, and the largest differences for ES were found at the highest elevations. Thus, our results suggest that the greatest uncertainty for simulating forest ES is due to differences between climate model chains, and we recommend using as many climate scenarios as possible when projecting future forest response to climate change. In addition, care should be taken when evaluating climate impacts at landscape locations that are known a priori to be sensitive to climate variation, such as high-elevation forests.