Improving forest management by implementing best suitable timber harvesting methods.

Efficient forest operations are required for the provision of biodiversity and numerous ecosystem services, such as wood production, carbon sequestration, protection against natural hazards and recreation. In numerous countries, under difficult terrain conditions, the costs of forest management and harvesting are not covered by timber revenue. One possible option to increase the cost-effectiveness of the forestry sector is the application of state-of-the-art harvesting and extraction techniques, so-called best suitable harvesting methods. We present a case study from Switzerland, where a lack of competitiveness in the forestry sector is of particular interest, with the aim of quantifying the efficiency gains if estimated best suitable harvesting methods were to be rigorously applied instead of the currently applied harvesting methods. For this purpose, we developed a spatial decision support system to allocate estimated best suitable harvesting methods to plots, while concurrently considering hauling route limitations, extraction route properties and stand characteristics. Our approach was based on productivity models and supported with expert-defined decision trees. The evaluation of the estimated best suitable harvesting methods and the comparison with the currently applied harvesting methods were completed for all 6500 National Forest Inventory (NFI) plots in Switzerland. We draw the following three major conclusions from our study: First, our modeling approach is an effective method to allocate estimated best suitable harvesting methods to NFI plots. Second, applying estimated best suitable harvesting methods would lead to cost reductions, in particular in the regions that include steep terrain and where harvesting mainly relies on cable- and air based extraction methods. Third, assuming an average timber price of 75 CHF m -3, 64 % instead of 52 % of the forest area could be harvested economically over the whole country if estimated best suitable methods were applied. This advantage would mainly be caused by a shift towards more mechanized harvesting methods. Improving the cost-effectiveness of the forestry sector is of high global relevance, as the increased use of domestic timber resources is a cost-efficient way to reduce atmospheric carbon emissions. The methodological framework described here was developed for Switzerland in particular, but it could be applied to Central Europe and other parts of Europe with a large amount of mountain forests.

The Swiss data cube, analysis ready data archive using earth observations of Switzerland.

Since the opening of Earth Observation (EO) archives (USGS/NASA Landsat and EC/ESA Sentinels), large collections of EO data are freely available, offering scientists new possibilities to better understand and quantify environmental changes. Fully exploiting these satellite EO data will require new approaches for their acquisition, management, distribution, and analysis. Given rapid environmental changes and the emergence of big data, innovative solutions are needed to support policy frameworks and related actions toward sustainable development. Here we present the Swiss Data Cube (SDC), unleashing the information power of Big Earth Data for monitoring the environment, providing Analysis Ready Data over the geographic extent of Switzerland since 1984, which is updated on a daily basis. Based on a cloud-computing platform allowing to access, visualize and analyse optical (Sentinel-2; Landsat 5, 7, 8) and radar (Sentinel-1) imagery, the SDC minimizes the time and knowledge required for environmental analyses, by offering consistent calibrated and spatially co-registered satellite observations. SDC derived analysis ready data supports generation of environmental information, allowing to inform a variety of environmental policies with unprecedented timeliness and quality.

Drone-based physiological index reveals long-term acclimation and drought stress responses in trees.

Monitoring early tree physiological responses to drought is key to understanding progressive impacts of drought on forests and identifying resilient species. We combined drone-based multispectral remote sensing with measurements of tree physiology and environmental parameters over two growing seasons in a 100-y-old Pinus sylvestris forest subject to 17-y of precipitation manipulation. Our goal was to determine if drone-based photochemical reflectance index (PRI) captures tree drought stress responses and whether responses are affected by long-term acclimation. PRI detects changes in xanthophyll cycle pigment dynamics, which reflect increases in photoprotective non-photochemical quenching activity resulting from drought-induced photosynthesis downregulation. Here, PRI of never-irrigated trees was up to 10 times lower (higher stress) than PRI of irrigated trees. Long-term acclimation to experimental treatment, however, influenced the seasonal relationship between PRI and soil water availability. PRI also captured diurnal decreases in photochemical efficiency, driven by vapour pressure deficit. Interestingly, 5 years after irrigation was stopped for a subset of the irrigated trees, a positive legacy effect persisted, with lower stress responses (higher PRI) compared with never-irrigated trees. This study demonstrates the ability of remotely sensed PRI to scale tree physiological responses to an entire forest and the importance of long-term acclimation in determining current drought stress responses.

Large-scale early-wilting response of Central European forests to the 2018 extreme drought.

The combination of drought and heat affects forest ecosystems by deteriorating the health of trees, which can lead to large-scale die-offs with consequences on biodiversity, the carbon cycle, and wood production. It is thus crucial to understand how drought events affect tree health and which factors determine forest susceptibility and resilience. We analyze the response of Central European forests to the 2018 summer drought with 10 × 10 m satellite observations. By associating time-series statistics of the Normalized Difference Vegetation Index (NDVI) with visually classified observations of early wilting, we show that the drought led to early leaf-shedding across 21,500 ± 2,800 km2 , in particular in central and eastern Germany and in the Czech Republic. High temperatures and low precipitation, especially in August, mostly explained these large-scale patterns, with small- to medium-sized trees, steep slopes, and shallow soils being important regional risk factors. Early wilting revealed a lasting impact on forest productivity, with affected trees showing reduced greenness in the following spring. Our approach reliably detects early wilting at the resolution of large individual crowns and links it to key environmental drivers. It provides a sound basis to monitor and forecast early-wilting responses that may follow the droughts of the coming decades.

Estimating below-canopy light regimes using airborne laser scanning: An application to plant community analysis.

Light is a key driver of forest biodiversity and functioning. Light regimes beneath tree canopies are mainly driven by the solar angle, topography, and vegetation structure, whose three-dimensional complexity creates heterogeneous light conditions that are challenging to quantify, especially across large areas. Remotely sensed canopy structure data from airborne laser scanning (ALS) provide outstanding opportunities for advancement in this respect. We used ALS point clouds and a digital terrain model to produce hemispherical photographs from which we derived indices of nondirectional diffuse skylight and direct sunlight reaching the understory. We validated our approach by comparing the performance of these indices, as well as canopy closure (CCl) and canopy cover (CCo), for explaining the light conditions experienced by forest plant communities, as indicated by the Landolt indicator values for light (L light) from 43 vegetation surveys along an elevational gradient. We applied variation partitioning to analyze how the independent and joint statistical effects of light, macroclimate, and soil on the spatial variation in plant species composition (i.e., turnover, Simpson dissimilarity, ß SIM) depend on light approximation methodology. Diffuse light explained L light best, followed by direct light, CCl and CCo (R2  = .31, .23, .22, and .22, respectively). The combination of diffuse and direct light improved the model performance for ß SIM compared with CCl and CCo (R2  = .30, .27 and .24, respectively). The independent effect of macroclimate on ß SIM dropped from an R 2 of .15 to .10 when diffuse light and direct light were included. The ALS methods presented here outperform conventional approximations of below-canopy light conditions, which can now efficiently be quantified along entire horizontal and vertical forest gradients, even in topographically complex environments such as mountains. The effect of macroclimate on forest plant communities is prone to be overestimated if local light regimes and associated microclimates are not accurately accounted for.

Stand inventory data from the 10-ha forest research plot in Uholka: 15 yr of primeval beech forest development.

Forests dominated by European beech (Fagus sylvatica L.) are among both the most widespread in Europe and the most intensely exploited globally. One of the largest remnants of unmanaged beech forests in Europe is the Uholka-Shyrokyi Luh forest in Transcarpathia, Ukraine, covering 8,800 ha of primeval forest. In 2000, a permanent forest plot of 10 ha has been established in the Uholka massif. All living and dead trees with a diameter at breast height (DBH) ≥ 60 mm were identified to species, DBH measured, stems tagged and mapped. Since then, the plot has been remeasured in 2005, 2010, and 2015. In total, 4,820 individual trees were measured with 14,116 individual measurements throughout all four inventories. In spring 2018, an Airborne Laser Scan was carried out, covering the Uholka-Shyrokyi Luh forest. This data set allows us to derive a high-resolution digital elevation model (DEM) of the plot area. European beech covers a share of ≈ 95% of the basal area (BA) of all living stems. While BA was relatively stable throughout all inventories (≈ 38 m2 /ha), the number of stems increased considerably between 2010 and 2015 from 290 to 430 stems/ha. Additionally, the proportion of beech stems decreased from 95% in 2010 to 86% in 2015. The continuity of the share of beech on BA and the decrease in number of stems can be traced back to disturbance events, which led to an increase of more light demanding species in the recruitment but did not alter the distribution of BA as these small trees contribute very little to BA. The data set allows for important insights into the development and the spatial and temporal dynamics of primeval beech forests. It can be used to quantify the demographic processes growth, mortality, and recruitment, and to study inter- and intraspecific effects on demographic rates, stand structure, and species composition. No copyright or proprietary restrictions are associated with the use of this data set other than citation of this Data Paper.

Climate-driven introduction of the Black Death and successive plague reintroductions into Europe.

The Black Death, originating in Asia, arrived in the Mediterranean harbors of Europe in 1347 CE, via the land and sea trade routes of the ancient Silk Road system. This epidemic marked the start of the second plague pandemic, which lasted in Europe until the early 19th century. This pandemic is generally understood as the consequence of a singular introduction of Yersinia pestis, after which the disease established itself in European rodents over four centuries. To locate these putative plague reservoirs, we studied the climate fluctuations that preceded regional plague epidemics, based on a dataset of 7,711 georeferenced historical plague outbreaks and 15 annually resolved tree-ring records from Europe and Asia. We provide evidence for repeated climate-driven reintroductions of the bacterium into European harbors from reservoirs in Asia, with a delay of 15 ± 1 y. Our analysis finds no support for the existence of permanent plague reservoirs in medieval Europe.

Driving factors of a vegetation shift from Scots pine to pubescent oak in dry Alpine forests.

An increasing number of studies have reported on forest declines and vegetation shifts triggered by drought. In the Swiss Rhone valley (Valais), one of the driest inner-Alpine regions, the species composition in low elevation forests is changing: The sub-boreal Scots pine (Pinus sylvestris L.) dominating the dry forests is showing high mortality rates. Concurrently the sub-Mediterranean pubescent oak (Quercus pubescens Willd.) has locally increased in abundance. However, it remains unclear whether this local change in species composition is part of a larger-scale vegetation shift. To study variability in mortality and regeneration in these dry forests we analysed data from the Swiss national forest inventory (NFI) on a regular grid between 1983 and 2003, and combined it with annual mortality data from a monitoring site. Pine mortality was found to be highest at low elevation (below 1000 m a.s.l.). Annual variation in pine mortality was correlated with a drought index computed for the summer months prior to observed tree death. A generalized linear mixed-effects model indicated for the NFI data increased pine mortality on dryer sites with high stand competition, particularly for small-diameter trees. Pine regeneration was low in comparison to its occurrence in the overstorey, whereas oak regeneration was comparably abundant. Although both species regenerated well at dry sites, pine regeneration was favoured at cooler sites at higher altitude and oak regeneration was more frequent at warmer sites, indicating a higher adaptation potential of oaks under future warming. Our results thus suggest that an extended shift in species composition is actually occurring in the pine forests in the Valais. The main driving factors are found to be climatic variability, particularly drought, and variability in stand structure and topography. Thus, pine forests at low elevations are developing into oak forests with unknown consequences for these ecosystems and their goods and services.

Filling the Eastern European gap in millennium-long temperature reconstructions.

Tree ring-based temperature reconstructions form the scientific backbone of the current global change debate. Although some European records extend into medieval times, high-resolution, long-term, regional-scale paleoclimatic evidence is missing for the eastern part of the continent. Here we compile 545 samples of living trees and historical timbers from the greater Tatra region to reconstruct interannual to centennial-long variations in Eastern European May-June temperature back to 1040 AD. Recent anthropogenic warming exceeds the range of past natural climate variability. Increased plague outbreaks and political conflicts, as well as decreased settlement activities, coincided with temperature depressions. The Black Death in the mid-14th century, the Thirty Years War in the early 17th century, and the French Invasion of Russia in the early 19th century all occurred during the coldest episodes of the last millennium. A comparison with summer temperature reconstructions from Scandinavia, the Alps, and the Pyrenees emphasizes the seasonal and spatial specificity of our results, questioning those large-scale reconstructions that simply average individual sites.

Accuracy assessment of digital surface models based on WorldView-2 and ADS80 stereo remote sensing data.

Digital surface models (DSMs) are widely used in forest science to model the forest canopy. Stereo pairs of very high resolution satellite and digital aerial images are relatively new and their absolute accuracy for DSM generation is largely unknown. For an assessment of these input data two DSMs based on a WorldView-2 stereo pair and a ADS80 DSM were generated with photogrammetric instruments. Rational polynomial coefficients (RPCs) are defining the orientation of the WorldView-2 satellite images, which can be enhanced with ground control points (GCPs). Thus two WorldView-2 DSMs were distinguished: a WorldView-2 RPCs-only DSM and a WorldView-2 GCP-enhanced RPCs DSM. The accuracy of the three DSMs was estimated with GPS measurements, manual stereo-measurements, and airborne laser scanning data (ALS). With GCP-enhanced RPCs the WorldView-2 image orientation could be optimised to a root mean square error (RMSE) of 0.56 m in planimetry and 0.32 m in height. This improvement in orientation allowed for a vertical median error of -0.24 m for the WorldView-2 GCP-enhanced RPCs DSM in flat terrain. Overall, the DSM based on ADS80 images showed the highest accuracy of the three models with a median error of 0.08 m over bare ground. As the accuracy of a DSM varies with land cover three classes were distinguished: herb and grass, forests, and artificial areas. The study suggested the ADS80 DSM to best model actual surface height in all three land cover classes, with median errors <1.1 m. The WorldView-2 GCP-enhanced RPCs model achieved good accuracy, too, with median errors of -0.43 m for the herb and grass vegetation and -0.26 m for artificial areas. Forested areas emerged as the most difficult land cover type for height modelling; still, with median errors of -1.85 m for the WorldView-2 GCP-enhanced RPCs model and -1.12 m for the ADS80 model, the input data sets evaluated here are quite promising for forest canopy modelling.