The objective of this study was to assess the use of unmanned aerial vehicle (UAV) data for modelling tree density and canopy height in young boreal forests stands. The use of UAV data for such tasks can be beneficial thanks to the high resolution and reduction of the time spent in the field. This study included 29 forest stands, within which 580 clustered plots were measured in the field. An area-based approach was adopted to which random forest models were fitted using the plot data and the corresponding UAV data and then applied and validated at plot and stand level. The results were compared to those of models based on airborne laser scanning (ALS) data and those from a traditional field-assessment. The models based on UAV data showed the smallest stand-level $RMSE$ values for mean height (0.56 m) and tree density (1175 trees ha⁻¹). The $RMSE$ of the tree density using UAV data was 50% smaller than what was obtained using ALS data (2355 trees ha⁻¹). Overall, this study highlighted that the use of UAVs for the inventory of forest stands under regeneration can be beneficial both because of the high accuracy of the derived data analytics and the time saving compared to traditional field assessments.

Climate change causes far‐reaching disruption in nature, where tolerance thresholds already have been exceeded for some plants and animals. In the short term, deer may respond to climate through individual physiological and behavioral responses. Over time, individual responses can aggregate to the population level and ultimately lead to evolutionary adaptations. We systematically reviewed the literature (published 2000–2022) to summarize the effect of temperature, rainfall, snow, combined measures (e.g., the North Atlantic Oscillation), and extreme events, on deer species inhabiting boreal and temperate forests in terms of their physiology, spatial use, and population dynamics. We targeted deer species that inhabit relevant biomes in North America, Europe, and Asia: moose, roe deer, wapiti, red deer, sika deer, fallow deer, white‐tailed deer, mule deer, caribou, and reindeer. Our review (218 papers) shows that many deer populations will likely benefit in part from warmer winters, but hotter and drier summers may exceed their physiological tolerances. We found support for deer expressing both morphological, physiological, and behavioral plasticity in response to climate variability. For example, some deer species can limit the effects of harsh weather conditions by modifying habitat use and daily activity patterns, while the physiological responses of female deer can lead to long‐lasting effects on population dynamics. We identified 20 patterns, among which some illustrate antagonistic pathways, suggesting that detrimental effects will cancel out some of the benefits of climate change. Our findings highlight the influence of local variables (e.g., population density and predation) on how deer will respond to climatic conditions. We identified several knowledge gaps, such as studies regarding the potential impact on these animals of extreme weather events, snow type, and wetter autumns. The patterns we have identified in this literature review should help managers understand how populations of deer may be affected by regionally projected futures regarding temperature, rainfall, and snow.

Natural regeneration of Norway spruce (Picea abies (L.) Karst.) is a relatively common practice in Norway on medium to low site indices. However, seedling establishment is often hampered by rapid regrowth of competing vegetation in scarified patches. The aim of our study was to examine the effect of coordinating scarification towards an expected seed-fall, by studying germination and seedling establishment in scarified patches of different age (fresh, one- and two-year-old). The experiment was conducted in two stands in southeast Norway that were clear-cut in 2007. Scarification was applied to subplots in autumn 2008–2010. To simulate seed-fall, seeds were sown in fresh scarification patches in spring 2009–2011, in one-year-old patches in 2010 and 2011, and in two-year-old patches in 2011. Both germination and seedling survival were negatively affected by the age of the scarified patches. Germination was higher, and mortality lower, at the small fern woodland site, compared with the bilberry woodland site. Sowing in fresh patches also resulted in increased height and root collar diameter of the seedlings compared with sowing in older patches. It is likely that the competing vegetation both on the site and in the scarification patches affected the growth of the seedlings. In conclusion, the age of the scarified patches affected both germination and mortality, as well as early growth of the seedlings.

Obtaining accurate estimates of national belowground and whole tree biomass is important to better understand the global carbon cycle and to quantify biomass stocks and changes. However, the availability of individual tree belowground biomass functions is generally low due to the difficulty of extracting roots. Allometric birch (Betula pubescens Ehrh. and Betula pendula Roth) biomass functions were derived from 67 trees for belowground and whole tree biomass using diameter at breast height (dbh) and height as the independent variables. The sampled trees spanned a dbh range from 4.0 to 45.5 cm and the functions provided a good fit to the data (RMSE = 14.2 kg for BG and 40.7 kg for whole tree with dbh as predictor). Belowground, total stem, live crown, and dead branch biomass comprised 29.2%, 52.2%, 18.1%, and 0.5% of the whole tree biomass, respectively. Observed root-to-shoot ratios were between 0.21 and 0.88 with a mean of 0.42. Comparisons with existing belowground birch biomass functions from Fennoscandia indicated considerable differences in estimates between existing functions. The derived data-set for belowground birch biomass is the largest in Fennoscandia and the developed functions are likely the best available for estimating national birch biomass stock and stock change in Norway.

Like large carnivores, hunters both kill and scare ungulates, and thus might indirectly affect plant performance through trophic cascades. In this study, we hypothesized that intensive hunting and enduring fear of humans have caused moose and other forest ungulates to partly avoid areas near human infrastructure (perceived hunting risk), with positive cascading effects on recruitment of trees. Using data from the Norwegian forest inventory, we found decreasing browsing pressure and increasing tree recruitment in areas close to roads and houses, where ungulates are more likely to encounter humans. However, although browsing and recruitment were negatively related, reduced browsing was only responsible for a small proportion of the higher tree recruitment near human infrastructure. We suggest that the apparently weak cascading effect occurs because the recorded browsing pressure only partly reflects the long‐term browsing intensity close to humans. Accordingly, tree recruitment was also related to the density of small trees 5–10 years earlier, which was higher close to human infrastructure. Hence, if small tree density is a product of the browsing pressure in the past, the cascading effect is probably stronger than our estimates suggest. Reduced browsing near roads and houses is most in line with risk avoidance driven by fear of humans (behaviorally mediated), and not because of excessive hunting and local reduction in ungulate density (density mediated).