Modelling bark beetle disturbances in a large scale forest scenario model to assess climate change impacts and evaluate adaptive management strategies

To study potential consequences of climate-induced changes in the biotic disturbance regime at regional to national scale we integrated a model of Ips typographus (L. Scol. Col.) damages into the large-scale forest scenario model EFISCEN. A two-stage multivariate statistical meta-model was used to upscale stand level damages by bark beetles as simulated in the hybrid forest patch model PICUS v1.41. Comparing EFISCEN simulations including the new bark beetle disturbance module against a 15-year damage time series for Austria showed good agreement at province level (R² between 0.496 and 0.802). A scenario analysis of climate change impacts on bark beetle-induced damages in Austria¿s Norway spruce [Picea abies (L.) Karst.] forests resulted in a strong increase in damages (from 1.33 Mm³ a¿1, period 1990¿2004, to 4.46 Mm³ a¿1, period 2095¿2099). Studying two adaptive management strategies (species change) revealed a considerable time-lag between the start of adaptation measures and a decrease in simulated damages by bark beetle

Potential stocks and increments of woody biomass in the European Union under different management and climate scenarios

BACKGROUND: Forests play an important role in the global carbon flow. They can store carbon and can also provide wood which can substitute other materials. In EU27 the standing biomass is steadily increasing. Increments and harvests seem to have reached a plateau between 2005 and 2010. One reason for reaching this plateau will be the circumstance that the forests are getting older. High ages have the advantage that they typical show high carbon concentration and the disadvantage that the increment rates are decreasing. It should be investigated how biomass stock, harvests and increments will develop under different climate scenarios and two management scenarios where one is forcing to store high biomass amounts in forests and the other tries to have high increment rates and much harvested wood. RESULTS: A management which is maximising standing biomass will raise the stem wood carbon stocks from 30 tC/ha to 50 tC/ha until 2100. A management which is maximising increments will lower the stock to 20 tC/ha until 2100. The estimates for the climate scenarios A1b, B1 and E1 are different but there is much more effect by the management target than by the climate scenario. By maximising increments the harvests are 0.4 tC/ha/year higher than in the management which maximises the standing biomass. The increments until 2040 are close together but around 2100 the increments when maximising standing biomass are approximately 50 % lower than those when maximising increments. Cold regions will benefit from the climate changes in the climate scenarios by showing higher increments. CONCLUSIONS: The results of this study suggest that forest management should maximise increments, not stocks to be more efficient in sense of climate change mitigation. This is true especially for regions which have already high carbon stocks in forests, what is the case in many regions in Europe. During the time span 2010-2100 the forests of EU27 will absorb additional 1750 million tC if they are managed to maximise increments compared if they are managed to maximise standing biomass. Incentives which will increase the standing biomass beyond the increment optimal biomass should therefore be avoided. Mechanisms which will maximise increments and sustainable harvests need to be developed to have substantial amounts of wood which can be used as substitution of non sustainable materials

Regeneration in gap models: priority issues for studying forest responses to climate change

Recruitment algorithms in forest gap models are examined with particular regard to their suitability for simulating forest ecosystem responses to a changing climate. The traditional formulation of recruitment is found limiting in three areas. First, the aggregation of different regeneration stages (seed production, dispersal, storage, germination and seedling establishment) is likely to result in less accurate predictions of responses as compared to treating each stage separately. Second, the relatedassumptions that seeds of all species are uniformly available and that environmental conditions are homogeneous, are likely to cause overestimates of future species diversity and forest migration rates. Third, interactions between herbivores (ungulates and insect pests) and forest vegetation are a big unknown with potentially serious impacts in many regions. Possible strategies for developing better gap model representations for the climate-sensitive aspects of each of these key areas are discussed. A working example of a relatively new model that addresses some of these limitations is also presented for each case. We conclude that better models of regeneration processes are desirable for predicting effects of climate change, but that it is presently impossible to determine what improvements can be expected without carrying out rigorous tests for each new formulation

Unraveling the drivers of intensifying forest disturbance regimes in Europe

Natural disturbances like wildfire, windthrow and insect outbreaks are critical drivers of composition, structure and functioning of forest ecosystems. They are strongly climate-sensitive, and are thus likely to be distinctly affected by climatic changes. Observations across Europe show that in recent decades, forest disturbance regimes have intensified markedly, resulting in a strong increase in damage from wind, bark beetles and wildfires. Climate change is frequently hypothesized as the main driving force behind this intensification, but changes in forest structure and composition associated with management activities such as promoting conifers and increasing standing timber volume (i.e. ‘forest change’) also strongly influence susceptibility to disturbances. Here, we show that from 1958 to 2001, forest change contributed in the same order of magnitude as climate change to the increase in disturbance damage in Europe's forests. Climate change was the main driver of the increase in area burnt, while changes in forest extent, structure and composition particularly affected the variation in wind and bark beetle damage. For all three disturbance agents, damage was most severe when conducive weather conditions and increased forest susceptibility coincided. We conclude that a continuing trend towards more disturbance-prone conditions is likely for large parts of Europe's forests, and can have strong detrimental effects on forest carbon storage and other ecosystem services. Understanding the interacting drivers of natural disturbance regimes is thus a prerequisite for climate change mitigation and adaptation in forest ecosystem management

Coupling a 3D patch model and a rockfall module to assess rockfall protection in mountain forests

Many forests in the Alps are acknowledged for protecting objects, such as (rail) roads, against rockfall. However, there is a lack of knowledge on efficient silvicultural strategies and interventions to maintain these forests at optimal protection level. Therefore, assessment tools are required that quantify the rockfall protection effect of forest stands over time, and thereby provide the ability to evaluate the necessity and effect of management interventions. This paper introduces such a tool that consists of a 3D rockfall module embedded in the patch based forest simulator PICUS. The latter is extended for this study with a new regeneration module. In a series of experiments the new combined simulation tool is evaluated with regard to parameter sensitivity, model intercomparison experiments with recently proposed algorithms from the literature, and the ability to respond realistically to different management regimes in rockfall protection forests. Results confirm the potential of the new tool for realistic simulation of rockfall activity in heterogeneous mountain forests, but point at the urgent need to improve the knowledge base on the interaction of understory and rockfall activity. Further work will focus on model validation against empirical rockfall data, and include reduced tree vitality due to damage from boulder collisions as well as the explicit consideration of downed dead woo

Potentials and limitations of using large-scale forest inventory data for evaluating forest succession models

Forest gap models have been applied widely to examine forest development under natural conditions and to investigate the effect of climate change on forest succession. Due to the complexity and parameter requirements of such models a rigorous evaluation is required to build confidence in the simulation results. However, appropriate data for model assessment are scarce at the large spatial and temporal scales of successional dynamics. In this study, we explore a data source for the evaluation of forest gap models that has been used only little in the past, i.e., large-scale National Forest Inventory data. The key objectives of this study were (a) to examine the potentials and limitations of using large-scale forest inventory data for evaluating the performance of forest gap models and (b) to test two particular models as case studies to derive recommendations for their future improvement. We used data from the first Swiss National Forest Inventory to examine the species basal area and tree numbers in different diameter classes simulated by the gap models ForClim (version 2.9.3) and PICUS (version 1.4) for forest types that are typical of mountain forests in Switzerland. The results showed the potential of data from large-scale forest inventories for evaluating model performance. Since this type of data is typically based on a large number of samples across environmental gradients, they are particularly suited for investigations at the general level of the dominant species based on stand basal area. However, the surprisingly small variability of juvenile trees (tree

Simulation tools for decision support to adaptive forest management in Europe

International audienc

Targeted Capture of Hundreds of Nuclear Genes Unravels Phylogenetic Relationships of the Diverse Neotropical Palm Tribe Geonomateae.

The tribe Geonomateae is a widely distributed group of 103 species of Neotropical palms which contains six ecologically important understory or subcanopy genera. Although it has been the focus of many studies, our understanding of the evolutionary history of this group, and in particular of the taxonomically complex genus Geonoma, is far from complete due to a lack of molecular data. Specifically, the previous Sanger sequencing-based studies used a few informative characters and partial sampling. To overcome these limitations, we used a recently developed Arecaceae-specific target capture bait set to undertake a phylogenomic analysis of the tribe Geonomateae. We sequenced 3,988 genomic regions for 85% of the species of the tribe, including 84% of the species of the largest genus, Geonoma. Phylogenetic relationships were inferred using both concatenation and coalescent methods. Overall, our phylogenetic tree is highly supported and congruent with taxonomic delimitations although several morphological taxa were revealed to be non-monophyletic. It is the first time that such a large genomic dataset is provided for an entire tribe within the Arecaceae. Our study lays the groundwork not only for detailed macro- and micro-evolutionary studies within the group, but also sets a workflow for understanding other species complexes across the tree of life