Forests cover about 1/3 of Europe’s land area and are an important source in providing goods and services such as timber, drinking water, biodiversity, and carbon storage. They are important for a bioeconomy to mitigate climate change effects by reducing greenhouse gas emissions from the combustion of fossil fuels. The purpose of this paper is to assess Europe’s potential wood supply by harvesting system. Gridded forest characteristics data are combined with other European spatially-explicit data. A set of eight mechanized harvesting systems is applied to assess the “forest available for wood supply” (FAWS) in Europe. The results show that 74.9% of the total forest area in Europe can be considered FAWS and has the potential to be harvested under the current economic and technical harvesting conditions. The remaining forest area is under legal protection (4.3%) or has limited accessibility with the current mechanized harvesting systems (20.8%). Around 79% of the FAWS can be accessed with ground-based machinery, and another 16% if their operation range is extended using special attachments (e.g., chains or band) or winch-assisted systems. Around 5% of the FAWS is only accessible by cable yarding machinery. With the fully mechanized harvesting systems (i) harvester and forwarder and (ii) winch-assisted harvester and winch-assisted forwarder, about 80% of the harvestable forest area and growing stock can potentially be utilized.

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In recent decades there has been an increasing demand by ecologists for harmonized climatic data at large spatial scales and spanning long periods. Here we present easyclimate, a software package to obtain daily climatic data at high resolution (0.0083º, ~1 km) with R. The package facilitates the downloading and processing of precipitation, minimum and maximum temperatures for Europe from 1950 to 2020. Using easyclimate and given a set of coordinates (points or polygons) and dates (days or years), the user can download the climatic information as a tidy table or a raster object. In this package we implemented Cloud-Optimized GeoTIFFs which provide access to daily climate data for thousands of sites/days within minutes, without having to download huge rasters. Daily climate data are not available in many of the current climate databases and are essential for many ecological research questions and applications, including the study of the effects of extreme climatic events related to late-spring frosts, heat waves, or dry periods on plant performance. easyclimate taps the potential for climatic data and enables multiple applications in forestry, ecological and vegetation studies across Europe.

Today, European forests face many challenges but also offer opportunities, such as climate change mitigation, provision of renewable resources, energy and other ecosystem services. Large-scale analyses to assess these opportunities are hindered by the lack of a consistent, spatial and accessible forest structure data. This study presents a freely available pan-European forest structure data set. Building on our previous work, we used data from six additional countries and consider now ten key forest stand variables. Harmonized inventory data from 16 European countries were used in combination with remote sensing data and a gap-filling algorithm to produce this consistent and comparable forest structure data set across European forests. We showed how land cover data can be used to scale inventory data to a higher resolution which in turn ensures a consistent data structure across sub-regional, country and European forest assessments. Cross validation and comparison with published country statistics of the Food and Agriculture Organization (FAO) indicate that the chosen methodology is able to produce robust and accurate forest structure data across Europe, even for areas where no inventory data were available.

Climate change, vegetation dynamics, human activities and forest management influence the occurrence of fires. This study investigated the spatio-temporal variability of the Vegetation Condition Index (VCI) and its influence on fire occurrence in three different land use types in Mount Kenya Forest Reserve and National Park (MKFRNP): National Park (NP), Forest Stations (FS) and Farmlands (FL). The study used MODIS satellite data to obtain the Normalized Difference Vegetation Index (NDVI), the VCI, the number of fires and the burnt area. The specific objectives of this research were (i) to examine the spatio-temporal variability of VCI, fire occurrence and burnt area in MKFRNP from 2003 to 2018 and (ii) to explore the relationship between VCI, fire occurrence and burnt area in different areas of the MKFRNP (NP, FS and FL). The findings show that even though fires occur throughout the year in MKFRNP, most of the fires occur during dry seasons. The relationship between spatio-temporal fire occurrence and VCI distribution is different for each land use type. In the FL, the probability of fire ignition and the number of fires per month was more or less the same irrespective of the VCI because of the traditional use of fire as a land management tool. However, the probability of fire ignition and the number of fires per month is high in the NP and FS when the VCI is below 50% (drought), especially in the dry seasons, when and where the impact of meteorological conditions and climate have much more impact than human activities. In addition to the efforts already made by communities, KFS and KWS in the fire fighting and monitoring system, satellite data can be useful to acquire accurate and timely information on the VCI and the likely spatio-temporal occurrence of fires in order to be prepared in the most fire-prone periods and improve fire management, the planning of resources and fire suppression activities in MKFRNP.