Date:
2018/06/13
Time:
17:30
Room:
A2 Wivi
Snag fall rates in Fennoscandian forests
(Oral)
, , ,
SEE PEER REVIEW
Snags (standing dead trees) are an integral component of natural boreal forests, serving multiple functions, including habitat for a variety of dead wood-dependent organisms, and as a dynamic carbon storage. As a result of intensive and long-term use of forests in Finland, Norway and Sweden, the amount of snags has drastically decreased from the levels encountered in the natural forests. Consequently, increasing the amount of snags is one important aim when restoring habitat diversity in managed forests. However, current information on the dynamics of snags and most importantly how long do they remain standing is fragmentary. Earlier research that has suffered from limited by data availability, has revealed a wide range in standing times of snags. This range has been variably linked to different factors, including climatic and edaphic conditions of the site, the tree species or its size, but comprehensive, large scale efforts on assessing dynamics of snags have not been conducted so far. Understanding snag dynamics and the factors that drive this variability would be essential for predicting snag dynamics and more efficiently incorporating them into forest management.
In this study, we will compile a large dataset of snag survival and fall in Fennoscandia, combining Finnish, Norwegian and Swedish national forest inventory (NFI) measurements on permanent sample plots since the mid-1990s, when systematic dead wood measurements began in these inventories. Using this dataset, our aim is to analyze the rates of snag fall, and their variability as a function of the characteristics of the snag, the site it grew on, and the climate.
For this, we will harmonize the datasets from the inventories of the three different countries, to create a single dataset for modeling snag dynamics. In the Norwegian NFI, individual snags are tracked through time as part of the measurement protocol, but for the Finnish and the Swedish NFIs we will first develop a piece-matching algorithm to link trees measured at one time with trees measured at the next inventory. We will then use mixed effects models to analyze snag fall rates, and the factors influencing their variability. Here, we report the first results of these analyses.