Norway spruce survival during bark beetle outbreak, with tree, stand and climatic variables

Published: 24 May 2022| Version 1 | DOI: 10.17632/nd799rkrtt.1
Nataliya Korolyova,
, Pavel Němčák,


The data set comprises tree-, stand-level and environmental attributes of 414 reference and 184 surviving Norway spruce (Picea abies) trees (598 trees in total) that sustained severe bark beetle (Ips typographus) outbreak in the Bohemian Forest region. The outbreak followed a series of windfalls in the 1980's and is ongoing. The study region spans two spatially disjunct conservation areas, the Bavarian Forest in Germany and Šumava National Park in Czechia. Reference trees refer to living trees sampled from the general population of spruce in the study area. Surviving trees termed "Last Trees Standing", or LTS, were identified using a combination of remote sensing analysis and field surveys. The variables in the data set include tree identification number (treeid), country, tree coordinates, survival status (0 - reference tree, 1 - surviving tree), self-shading ratio, diameter at breast height (dbh) (cm), pre-outbreak stand density (ha), and climatic water balance. Google Earth Pro (GE) 15 cm resolution time series photography available from 2000 to 2019 was used to detect scattered LTS occurrences in the study area. Each image of extant tree was visually and systematically examined to measure projections of the overall shadow length and crown length. Self-shading was calculated as a ratio of crown length to overall tree height derived from measurements of corresponding shadow projections in GE. GE-derived measurements and LTS positions were ground-truthed during field survey. We developed an allometric model to estimate tree diameter at breast height (dbh) from associated GE-derived crown projection area for all LTS. The density of beetle-killed trees within areas of disturbed spruce forest was estimated using spectral and regression analyses. We first classified a Landsat satellite image of the Bohemian Forest to delineate the total areal extent of insect disturbed forest. We then used a regression model to estimate the density of killed trees within the disturbance area. A climatic water balance was calculated as the difference between water supply from precipitation and maximum water losses associated with potential evapotranspiration (PET). PET was estimated using radiation-based method which integrates temperature. We computed global solar radiation using the Area Solar Radiation function in ArcGIS 10.8 and 25 m digital elevation model from Copernicus. Monthly temperature and precipitation values for each year of the 30-year analysis window were derived from two gridded climate datasets: CHELSA (30 arcsec) for the period 1990 to 2013, and E-OBS (0.1°) for 2014 to 2019. The resulting monthly water budget was summed over growing season (May to September) for each year, and averaged over the 30-year analysis period.



Ceska Zemedelska Univerzita v Praze Fakulta lesnicka a drevarska


Remote Sensing, Picea, Survival Analysis, Density, Disturbance Ecology, Forest Management, Forest Ecology, Forest Pest, Climate Change, Drought, Germany, Czech Republic, Maximum Likelihood Estimation, National Park, Density Estimation Modeling, Forest Entomology, Forest Ecosystem, Multivariate Logistical Regression, Beetle, Forest, Likelihood Approach, Forest Health