Quantifying the effect of persistent dryer climates on forest productivity and implications for forest planning:a case study in northern Germany

Background: Forest management decisions are based on expectations of future developments. For sound decisions it is essential to accurately predict the expected values in future developments and to account for their inherent uncertainty,for example the impact of climate change on forests. Changing climatic conditions affect forest productivity and alter the risk profile of forests and forest enterprises. Intensifying drought stress is seen as one major risk factor threatening forest management in the north German lowlands. Drought stress reduces tree growth and vitality and might even trigger mortality. But so far, it is not possible to quantify effects of a persistent dryer climate on forest productivity at a level suitable for forest management.Methods: We apply a well-established single-tree forest growth simulator to quantify the effect of persistent dryer climates on future forest productivity. We analyse the growth of Scots pine(Pinus sylvestris L.), European beech(Fagus sylvatico L.) and oak(Quercus robur L. and Quercus petraea(Matt.) Liebl.) in two forest regions in the north German lowlands for a time interval of 60 years until 2070. The growth response under three different climate projections is compared to a baseline scenario.Results: The results show clear differences in volume increment to persistent dryer climates between tree species. The findings exhibit regional differences and temporal trends. While mean annual increment at biological rotation age of Scots pine and oak predominantly benefits from the projected climate conditions until 2070, beech might suffer losses of up to 3 m^3·ha^(-1)yr^(-1) depending on climate scenario and region. However, in the projection period2051 to 2070 the uncertainty ranges comprise positive as well as negative climatic effects for all species.Conclusions: The projected changes in forest growth serve as quantitative contributions to provide decision support in the evaluation of, for example, species future site suitability and timber supply assessments. The analysis of productivity changes under persistent dryer climate complements the drought vulnerability assessment which is applied in practical forestry in northwestern Germany today. The projected species' productivity has strong implications for forest management and the inherent uncertainty needs to be accounted for.

Charcoal kiln sites, associated landscape attributes and historic forest conditions:DTM-based investigations in Hesse(Germany)

Background： An examination of the distribution of ancient charcoal kiln sites in the forest landscape seems to be worthwhile, since general trends in the selection of suitable kiln site locations in the past might become obvious. In this way forest landscape elements with a more intense usage by charcoal burning can be identified. By doing this, we can expect to gain information on the former condition and tree species composition of woodland. Investigations on the spatial distribution of charcoal kiln sites in relation to landscape attributes are sparse, however, probably due to the high on-site mapping effort. The outstanding suitability of LiDAR-derived digital terrain models （DTMs） for the detection of charcoal kiln sites has been recently proved. Hence, DTM-based surveys of charcoal kiln sites represent a promising attempt to fill this research gap. Methods： Based on DTM-based surveys, we analyzed the spatial distribution of charcoal kiln sites in two forest landscapes in the German federal state of Hesse： Reinhardswald and Kellerwald-Edersee National Park. In doing so, we considered the landscape attibutes ＂tree species composition＂, ＂water supply status＂, ＂nutrient supply status＂, ＂soil complex classes＂, ＂altitude＂, ＂exposition＂, and ＂inclination＂. Results： We found that charcoal kiln sites were established preferably on hillside locations that provided optimal growing and regeneration conditions for European beech （Fagus sylvatico） due to their acidic brown soils and sufficient water supply. These results are in line with instructions for the selection of appropriate kiln site locations, found in literature from the 18th to the 19th century. Conclusions： We conclude that there were well-stocked, beech-dominated deciduous forest stands in northern Hesse before 1800, particularly at poorly accessible hillside locations. These large stocks of beech wood were utilized by the governments of the different Hessian territories through the establishment of ironworks and hammer mills. Our argumentation is well in line with findings which underline that not all Hessian forests were overexploited in the 18th century. Frequently repeated complaints about ＂wood shortage＂ seemed to be more a political instrument than reality, not only in Hesse, but all over Europe. Consequently, a differentiated assessment of woodland conditions in proto-industrial times is strictly advised, even if contemporary sources draw a dark picture of the historic situation.

Assessing citizen science opportunities in forest monitoring using probabilistic topic modelling

Background： With mounting global environmental, social and economic pressures the resilience and stability of forests and thus the provisioning of vital ecosystem services is increasingly threatened. Intensified monitoring can help to detect ecological threats and changes earlier, but monitoring resources are limited. Participatory forest monitoring with the help of ＂citizen scientists＂ can provide additional resources for forest monitoring and at the same time help to communicate with stakeholders and the general public. Examples for citizen science projects in the forestry domain can be found but a solid, applicable larger framework to utilise public participation in the area of forest monitoring seems to be lacking. We propose that a better understanding of shared and related topics in citizen science and forest monitoring might be a first step towards such a framework. Methods： We conduct a systematic meta-analysis of 1015 publication abstracts addressing ＂forest monitoring＂ and ＂citizen science＂ in order to explore the combined topical landscape of these subjects. We employ ＇topic modelling an unsupervised probabilistic machine learning method, to identify latent shared topics in the analysed publications. Results： We find that large shared topics exist, but that these are primarily topics that would be expected in scientific publications in general. Common domain-specific topics are under-represented and indicate a topical separation of the two document sets on ＂forest monitoring＂ and ＂citizen science＂ and thus the represented domains. While topic modelling as a method proves to be a scalable and useful analytical tool, we propose that our approach could deliver even more useful data if a larger document set and full-text publications would be available for analysis. Conclusions： We propose that these results, together with the observation of non-shared but related topics, point at under-utilised opportunities for public participation in forest monitoring. Citizen science could be applied as a versatile tool in forest ecosystems monitoring, complementing traditional forest monitoring programmes, assisting early threat recognition and helping to connect forest management with the general public. We conclude that our presented approach should be pursued further as it may aid the understanding and setup of citizen science efforts in the forest monitoring domain.

Modelling the population fluctuation of winter moth and mottled umber moth in central and northern Germany

Background: Winter moth(Operophtera brumata) and mottled umber moth(Erannis defoliaria) are forest Lepidoptera species characterized by periodic high abundance in a 7–11 year cycle. During outbreak years they cause severe defoliation in many forest stands in Europe. In order to better understand the spatio-temporal dynamics and elucidate possible influences of weather, stand and site conditions, a generalized additive mixed model was developed. The investigated data base was derived from glue band catch monitoring stands of both species in Central and North Germany. From the glue bands only female moth individuals are counted and a hazard code is calculated. The model can be employed to predict the exceedance of a warning threshold of this hazard code which indicates a potential severe defoliation of oak stands by winter moth and mottled umber in the coming spring.Results: The developed model accounts for specific temporal structured effects for three large ecoregions and random effects at stand level. During variable selection the negative model effect of pest control and the positive model effects of mean daily minimum temperature in adult stage and precipitation in early pupal stage were identified.Conclusion: The developed model can be used for short-term predictions of potential defoliation risk in Central and North Germany. These predictions are sensitive to weather conditions and the population dynamics. However, a future extension of the data base comprising further outbreak years would allow for deeper investigation of the temporal and regional patterns of the cyclic dynamics and their causal influences on abundance of winter moth and mottled umber.

Success factors for high-quality oak forest(Quercus robur, Q. petraea) regeneration

Background: Within the framework of close-to-nature forestry, oak forest(Quercus robur, Q. petraea) regeneration techniques that consider both silvicultural and nature conservation demands have become a very important issue.While there are many experimental and local studies that aim at disentangling the relationships between different environmental and silvicultural factors and the success of oak regeneration, systematic supra-regional studies at the greater landscape level are missing so far.Against this background, the first objective(a) of this study was to present an efficient and sufficiently accurate sampling scheme for supra-regional forest regrowth inventories, which we applied to young oaks stands. The second, and major, objective(b) was to identify the crucial success factors for high-quality oak forest regeneration in northwest Germany.Results: Objective(a): Factors that have been identified as potentially crucial for the success or failure of oak regeneration were either included in a field inventory procedure or extracted from forest inventory databases. We found that the collected data were suitable to be analyzed in a three-step success model, which was aimed at identifying the crucial success factors for high-quality oak forest regeneration.Objective(b): Our modeling procedure, which included a Bayesian estimation approach with spike-and-slab priors,revealed that competitive pressure from the secondary tree species was the most decisive success factor;no competition, or low competition by secondary tree species appeared to be particularly beneficial for the success of high-quality oak regeneration. Also fencing and the absence of competitive vegetation(weeds, grass, bracken)seemed to be beneficial factors for the success of oak regeneration.Conclusions: Trusting in biological automation was found to be mostly useless regarding economically viable oak forest regeneration. To efficiently organize oak regeneration planning and silvicultural decision-making within a forest enterprise, it is strongly recommended to initially evaluate the annual financial and personnel capacities for carrying out young growth tending or pre-commercial thinning and only then to decide on the extent of regenerated oak stands. Careful and adaptive regeneration planning is also indispensable to secure the long-term ecological continuity in oak forests. Oak regeneration should therefore preferably take place within the close vicinity of old oak stands or directly in them. The retention of habitat trees is urgently advised.

Longitudinal height-diameter curves for Norway spruce, Scots pine and silver birch in Norway based on shape constraint additive regression models

Background： Generalized height-diameter curves based on a re-parameterized version of the Korf function for Norway spruce （Piceo abies （L.） Karst.）, Scots pine （Pinus sylvestris L.） and silver birch （Betula pendula Roth） in Norwa are presented. The Norwegian National Forest Inventory （NFI） is used as data base for estimating the model parameters. The derived models are developed to enable spatially explicit and site sensitive tree height imputatio in forest inventories as well as future tree height predictions in growth and yield scenario simulations. Methods： Generalized additive mixed models （gamm） are employed to detect and quantify potentially non-linear effects of predictor variables. In doing so the quadratic mean diameter serves as longitudinal covariate since stand ag as measured in the NFI, shows only a weak correlation with a stands developmental status in Norwegian forests. Additionally the models can be locally calibrated by predicting random effects if measured height-diameter pairs are available. Based on the model selection of non-constraint models, shape constraint additive models （scare） were fit tc incorporate expert knowledge and intrinsic relationships by enforcing certain effect patterns like monotonicity. Results： Model comparisons demonstrate that the shape constraints lead to only marginal differences in statistical characteristics but ensure reasonable model predictions. Under constant constraints the developed models predict increasing tree heights with decreasing altitude, increasing soil depth and increasing competition pressure of a tree. / two-dimensional spatially structured effect of UTM-coordinates accounts for the potential effects of large scale spatial correlated covariates, which were not at our disposal. The main result of modelling the spatially structured effect is lower tree height prediction for coastal sites and with increasing latitude. The quadratic mean diameter affects both the level and the slope of the height-diameter curve and both effects are positive. Conclusions： In this investigation it is assumed that model effects in additive modelling of height-diameter curves which are unfeasible and too wiggly from an expert point of view are a result of quantitatively or qualitatively limited data bases. However, this problem can be regarded not to be specific to our investigation but more general since growth and yield data that are balanced over the whole data range with respect to all combinations of predictor variables are exceptional cases. Hence, scare may provide methodological improvements in several applications by combining the flexibility of additive models with expert knowledge.