Maris Hordo

Estimating tree survival: a study based on the Estonian Forest Research Plots Network

Tree survival, as affected by tree and stand variables, was studied using the Estonian database of permanent forest research plots. The tree survival was examined on the basis of remeasurements during the period 1995–2004, covering the most common forest types and all age groups. In this study, the influence of 35 tree and stand variables on tree survival probability was analyzed using the data of 31 097 trees from 236 research plots. For estimating individual tree survival probability, a logistic model using the logit-transformation was applied. Tree relative height had the greatest effect on tree survival. However, different factors were included into the logistic model for different development stages: tree relative height, tree relative diameter, relative basal area of larger trees and relative sparsity of a stand for young stands; tree relative height, relative basal area of larger trees and stand density for middle-aged and maturing stands; and tree relative height and stand density for mature and overmature stands. The models can be used as preliminary sub-components for elaboration of a new individual tree based growth simulator.

AUGUST TO JULY PRECIPITATION FROM TREE RINGS IN THE FOREST-STEPPE ZONE OF CENTRAL SIBERIA (RUSSIA)

ABSTRACT The goal of this research report is to describe annual precipitation reconstruction from Pinus sylvestris trees on three sites in the Abakan region, located in the Minusinsk Depression, at the confluence of the Yenisei and Abakan Rivers, Russia. The study was performed during the 4th annual international summer course “Tree Rings, Climate, Natural Resources and Human Interaction” held in Abakan, 5-19 August 2013. The reconstruction, for the 12-month total precipitation ending in July of the growth year, is based on a reliable and replicable statistical relationship between precipitation and tree-ring growth, and shows climate variability on both interannual and interdecadal time scales. The regional tree-ring chronology accounts for 56% of the variance of observed annual precipitation in a linear regression model, with the strongest monthly precipitation signal concentrated in May and June of the current growing season. Composite 500 mb height-anomaly maps suggest that the tree-ring data from this site, supplemented by other regional tree-ring data, could yield information on long-term atmospheric circulation variability over the study area and surrounding region.

Monitoring and modeling of forest ecosystems: the Estonian Network of Forest Research Plots / Metsaökosüsteemide seire ja modelleerimine metsa kasvukäigu püsiproovitükkide võrgustiku abil

Abstract Forest research has long traditions in Estonia that can be traced back to the 19th century. Data from long-term forest experiments are available since 1921. The first studies mainly focused on silvicultural treatments and application of such data for understanding and modeling ecological processes was limited. The Department of Forest Management of the Estonian University of Life Sciences started to develop the Estonian Network of Forest Research Plots (ENFRP) in 1995. Since then, plots have been continuously re-measured with 5-year interval. Approximately 100-150 permanent sample plots were measured annually. In 2014, the long-term research network consisted of 729 permanent sample plots, of which 699 have been re-measured at least once, 667 plots - twice and 367 plots - three times. The total number of trees recorded in the network database amounts to 130,479. The plots are systematically distributed throughout the country. Detailed dendrometric measurements including tree spatial distribution are part of the survey protocol. Initially the network was set up to produce suitable data for development of individual tree growth models for Estonia. The significance of the network for the Estonian forest research is continuously increasing and nowadays ENFRP is recognized as an important national research infrastructure.

MERIS GPP/NPP product for Estonia: I. Algorithm and preliminary results of simulation / MERIS’e GPP/NPP tulem Eesti jaoks: I. Algoritm ja mudelarvutuste esialgsed tulemused

Abstract. A light use efficiency (LUE) type model named EST_PP to simulate the yearly gross primary production (GPP) and net primary production (NPP) of Estonian land on a 1 km2 grid is described. The model is based on MERIS (MEdium Resolution Imaging Spectrometer) satellite images to describe the fraction of photosynthetically active radiation (fAPAR) and leaf area index (LAI) as well as meteorological reanalysis datasets on 11 km2 grid produced by Estonian Meteorological Institute (EMHI) and Tartu University (TU) by means of the HIRLAM (High Resolution Limited Area Model) numerical weather prediction model. The land cover map of Estonia needed for the model was derived using DMCii (Disaster Monitoring Constellation International Imaging) SLIM-6-22 (Surrey Linear Imager - 6 channel - 22 m resolution) images and ancillary information. The EST_PP model was run for the period from years 2003 to 2011. The results of GPP and NPP simulation are compared with the available global MODIS (Moderate Resolution Imaging Spectroradiometer) GPP/NPP product and with the Estonian statistical data on yearly volume increment in forests and on yield of agricultural crops. The NPP simulation results on coniferous and deciduous forests are compared with the data from tree ring analyses from different counties. These comparisons show us that the simulated country average yearly NPP values for Estonian forests agree reasonably well with the indirect estimates from other sources, taking into account the rather high uncertainty of the model predictions, uncertainty of forest inventory-based estimates and limited representativity of existing tree ring data. However, problems arise with the ability of present versions of EST_PP and MODIS NPP models to adequately simulate the regional differences of productivity and of variability of productivity in different years. The model needs some modification and the basic LUE principles to be tested in Estonia. Nevertheless, the MODIS NPP and EST_PP models offer additional possibilities to map yearly productivity and carbon sequestration by Estonian vegetation. There is a perspective to add the model-simulated NPP values into the national inventory datasets.