Self-learning growth simulator for modelling forest stand dynamics in changing conditions

Finnish forest structures vary from even-aged planted forests to two- and multi-storied mixed stands. Also, the range of silvicultural systems in use has increased because thinning from above and continuous cover management are gaining popularity. The data currently available for modelling stand dynamics are insufficient to allow the development of unbiased and reliable models for the simulation of all possible transitions between various current and future stand conditions. Therefore, the models should allow temporal and regional calibration along the accumulation of new information on forest development. If the calibration process is automated, the simulators that use these models constitute a self-Learning system that adapts to the properties of new data on stand dynamics. The current study first developed such a model set for stand dynamics that is technically suitable for simulating the stand development in all stand structures, silvicultural systems and their transitions. The model set consists of individual-tree models for diameter increment and survival and a stand-Level model for ingrowth. The models were based on the permanent sample plots of the 10th and 11th national forest inventories of Finland. Second, a system for calibrating the models based on additional data was presented. This optimization-based system allows different types and degrees of calibration, depending on the intended use of the models and the amount of data available for calibration. The calibration method was demonstrated with two external datasets where a set of sample plots had been measured two times at varying measurement intervals.Peer reviewe

Kaavoituksen vaikutukset metsätalouteen - esimerkkejä Etelä-Suomesta

201

Sources and types of uncertainties in the information on forest-related ecosystem services

201

Synthesis on bioeconomy monitoring systems in the EU Member States - indicators for monitoring the progress of bioeconomy

The urgent need to shift our economy towards a more sustainable, resource-efficient economy based on renewable resources that either makes less use of fossil resources or dispenses with them entirely, the so called bioeconomy, has been recognized all over Europe. As a result, many EU Member States (EU MS) have formulated national and regional bioeconomy strategies, related policies or initiatives. An important tool for the successful implementation of a strategy is the monitoring and evaluation of the success of the measures undertaken to reach the strategy´s goals. The EC review report of the EU Bioeconomy strategy concluded the need for better monitoring and assessment frameworks, “new actions are needed to develop relevant indicators and scientific evidence for policy making, and to implement a more holistic monitoring and assessment framework” (EC 2017). However, up to now, there is no commonly agreed set of indicators to measure the bioeconomy at EU level. Because the main drivers for the transition towards a bioeconomy often strongly vary between EU MS on the country-specific economic and ecological settings, legal framework, and social demands, also the national or regional bioeconomy strategies vary in their goals and measures. Consequently, proxies and indicators used to measure the development of a national bioeconomy or the success of a bioeconomy strategy depend on the national goals, and are therefore often not applicable in any other country. Nevertheless, synchronizing the national bioeconomy monitoring-activities is necessary to ensure comparability of the results of the national monitoring systems. As a first step towards a common European bioeconomy monitoring-activity, it is crucial to get an overview over the numerous scattered ongoing monitoring activities at EU MS level. Therefore, there is the need for an overview study presenting information on existing approaches of monitoring bioeconomy strategies in the EU MS. This report presents an overview of existing bioeconomy strategies, policies or related initiatives and indicators to monitor and assess these at EU MS level, and the importance of existing bioeconomy sectors at national level. Furthermore, it presents the existing or needed most suitable bioeconomy key indicators and related indicators, and their respective data availability, for assessing and monitoring the progress of a bioeconomy at national level. The identified most suitable bioeconomy indicators important and feasible at the national context, can contribute to the further discussions when setting the frame for the development of a common EU bioeconomy monitoring system.201

Can models for forest attributes based on airborne laser scanning be generalized for different silvicultural management systems?

In Finland, interest in continuous cover forestry (CCF) has increased rapidly in recent years. During those years CCF has been examined from various viewpoints but not from the perspective of forest inventories. This holds especially true for applications based on remote sensing. Conversely, airborne laser scanning (ALS) data have been widely used to predict forest characteristics such as size distribution and vertical forest structure, which are closely related to the forest information needs of CCF. In this study we used the area-based approach to predict a set of stand attributes from ALS data (5 pulses per m2) in a CCF forest management experiment in Katajama & BULL;ki, eastern Finland. In addition to the CCF stands, the experiment included shelterwood stands and untreated stands. The predicted attributes included volume, biomass, basal area, number of stems, mean diameter, Lorey's height, dominant height, standing dead wood volume, parameters of the theoretical stem diameter distribution model, understory height and number of understory stems. Our main aim was to test whether the same model could be used across different management systems. The accuracy of the attributes predicted for the CCF stands was compared with the predictions for the other management systems in the same experiment. We also compared and discussed our results in relation to the even-aged stand attribute predictions that were conducted by using separate operational forest data collected from sites surrounding Katajama & BULL;ki. The results showed that forest data from the different management systems could be combined into a single model of a stand attribute, i.e., ALS metrics were found to be suitable for comparing different management systems in regard to differences in forest structure. The accuracy of the predicted attributes in the CCF plots was comparable to that of the other management alternatives in the experiment. The accuracy was also comparable to that of even-aged forests. The results of this study were promising; the stand attributes of CCF-managed forests could be predicted analogously to those of other management systems. This indicates that for the purposes of forest inventories there may not be a need to stratify forest lands by management system. It should be noted, however, that the study area was relatively small, that the forest stands were harvested in the 1980 s, and that the attributes may not have been completely exhaustive for CCF

Finland’s forests 2018

Luken kirjat, raportit, oppaat ja esitteet201

The effect of snow depth on movement rates of GPS-collared moose

During deep snow conditions, wildlife must balance between minimizing movements to conserve energy while seeking high amounts of browse to gain the energy. Knowledge of how snow begins to hinder their movements is therefore vital when predicting their wintertime behavior. We assessed the phenomenon with moose. Movement data from 122 GPS-collared moose were integrated with snow depth data from designated measurement stations. The effects of increasing snow depths on moose movement rates were then modeled with spline regression. The study was conducted in Finland, between 2009 and 2011. The moose were known for their sex and for the presence of calf at heel. On average, the movement rates decreased sharply until snow depths of ca. 30–40 cm, after which further significant decreases were not seen. The movement rates decreased from several kilometers per day to less than 500 m per day. Moose in the northernmost study area with the deepest snow covers moved as much as the moose in the other areas with less snow. Although we saw differences in the movement rates between males and females, differences between individuals were markedly higher than those caused by sex or a calf at heel. Moose are keystone species whose heavy browsing, especially during winter, can have profound effects on vegetation and forest regeneration. As snow covers in large parts of the boreal zone are predicted to decrease due to warming climate, the wintertime movements of moose and how they affect the local vegetation will remain relevant questions

Lapin metsävaratietoa, Valtakunnan metsien inventointi Lapissa

201

Catering Information Needs from Global to Local Scales-Potential and Challenges with National Forest Inventories

Forest information is needed at global, national and local scales. This review aimed at providing insights of potential of national forest inventories (NFIs) as well as challenges they have to cater to those needs. Within NFIs, the authors address the methodological challenges introduced by the multitude of scales the forest data are needed, and the challenges in acknowledging the errors due to the measurements and models in addition to sampling errors. Between NFIs, the challenges related to the different harmonization tasks were reviewed. While a design-based approach is often considered more attractive than a model-based approach as it is guaranteed to provide unbiased results, the model-based approach is needed for downscaling the information to smaller scales and acknowledging the measurement and model errors. However, while a model-based inference is possible in small areas, the unknown random effects introduce biased estimators. The NFIs need to cater for the national information requirements and maintain the existing time series, while at the same time providing comparable information across the countries. In upscaling the NFI information to continental and global information needs, representative samples across the area are of utmost importance. Without representative data, the model-based approaches enable provision of forest information with unknown and indeterminable biases. Both design-based and model-based approaches need to be applied to cater to all information needs. This must be accomplished in a comprehensive way In particular, a need to have standardized quality requirements has been identified, acknowledging the possibility for bias and its implications, for all data used in policy making.Peer reviewe

Lapin metsävarat ja hakkuumahdollisuudet

201