Parameter recovery vs. parameter prediction for the Weibull distribution validated for Scots pine stands in Finland

201

Decline of the boreal willow grouse (Lagopus lagopus) has been accelerated by more frequent snow-free springs

Climate change has influenced a range of species across the globe. Yet, to state a noted decline in the abundance of a given species as a consequence of a specific environmental change, for instance, spatially explicit long-term data are a prerequisite. This study assessed the extent to which prolonged snow-free periods in autumn and spring have contributed to the decline of the willow grouse, the only forest grouse changing into a white winter plumage. Time-series data of willow grouse numbers from summer surveys across the study area were integrated with local data on weather (snow cover), mammalian predator abundance and hunting intensity. Modelling was conducted with a hierarchical Bayesian Poisson model, acknowledging year-, area- and location-specific variability. The results show that while willow grouse numbers had decreased continuously across the study landscapes, the decrease was accelerated at the sites where, and during the years when the preceding April was the most snow-free. This indicates a mismatch between the change into a white winter plumage and the presence of snow, turning the bird into an ill-camouflaged prey. The results thus also confirm past hypotheses where local declines of the species have been attributed to prolonged snow-free periods. Across our study area, autumns and springs have become more snow-free, and the trend has been predicted to continue. Thus, in addition to conservation actions, the future of a species such as the willow grouse is also dependent on its ability to adapt to the changed environmental conditions.202

Key structural features of Boreal forests may be detected directly using L-moments from airborne lidar data

This article introduces a novel methodology for automated classification of forest areas from airborne laser scanning (ALS) datasets based on two direct and simple rules: L-coefficient of variation Lcv=0.5 and L-skewness Lskew=0, thresholds based on descriptors of the mathematical properties of ALS height distributions. We observed that, while Lcv>0.5 may represent forests with large tree size inequality, Lskew>0 can be an indicator for areas lacking a closed dominant canopy. Lcv=0.5 discriminated forests with trees of approximately equal sizes (even tree size classes) from those with large tree size inequality (uneven tree size classes) with kappa κ = 0.48 and overall accuracy OA = 92.4%, while Lskew=0 segregated oligophotic and euphotic zones with κ = 0.56 and OA = 84.6%. We showed that a supervised classification could only marginally improve some of these accuracy results. The rule-based approach presents a simple method for detecting structural properties key to tree competition and potential for natural regeneration. The study was carried out with low-density datasets from the national program on ALS surveying of Finland, which shows potential for replication with the ALS datasets typically acquired at nation-wide scales. Since the presented method was based on deductive mathematical rules for describing distributions, it stands out from inductive supervised and unsupervised classification methods which are more commonly used in remote sensing. Therefore, it presents an opportunity for deducing physical relations which could partly eliminate the need for supporting ALS applications with field plot data for training and modelling, at least in Boreal forest ecosystems

Vegetation structure and photosynthesis respond rapidly to restoration in young coastal fens

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Understanding uncertainty in forest resources maps

Maps of forest resources and other ecosystem services are needed for decision making at different levels. However, such maps are typically presented without addressing the uncertainties. Thus, the users of the maps have vague or no understanding of the uncertainties and can easily make wrong conclusions. Attempts to visualize the uncertainties are also rare, even though the visualization would be highly likely to improve understanding. One complication is that it has been difficult to address the predictions and their uncertainties simultaneously. In this article, the methods for addressing the map uncertainty and visualize them are first reviewed. Then, the methods are tested using laser scanning data with simulated response variable values to illustrate their possibilities. Analytical kriging approach captured the uncertainty of predictions at pixel level in our test case, where the estimated models had similar log-linear shape than the true model. Ensemble modelling with random forest led to slight underestimation of the uncertainties. Simulation is needed when uncertainty estimates are required for landscape level features more complicated than small areas

Mixed linear and non-linear tree volume models with regional parameters to main tree species in Finland

The volume models that have been used in Finland for the last 40 years, while generally well thought-out, exhibit an illogical behaviour for small trees. In recent studies, tree stem form was observed to have changed in time and also involve spatial variation attributable to environmental factors. It is yet unclear how the stem taper has actually changed. To overcome these problems, we fitted a completely new set of volume and taper curve models and examined whether this change is attributable to the changes in management and environmental factors rather than to measurement errors in the previously used datasets. For the latter, we added a dataset into the analysis, which was smaller but of higher quality due to the destructive nature of the stem taper measurements. We aim at (1) developing a new non-linear variable form factor volume function that works with trees of all sizes, (2) improving the description of the variation of the stem form in time and space by including temperature sum and soil type as predictors, (3) understanding the changes in the stem form by fitting new taper curve models and (4) improving the statistical properties of the predictions by using mixed model techniques and by addressing the effect of parameter uncertainty. To assess the impact of renewing the models, we (5) predicted the mean volume and its confidence interval with each model for forest inventory data at country level. The results show that the tree stem form has a spatial trend that can be described with the temperature sum. Moreover, the changes in stem form also have a spatial trend, with largest changes in Lapland. The difference is mostly observable in the lowest part of the stem, and it is especially large in the largest pines. We conclude that environmental variables can help to improve national stem taper functions in countries with pronounced environmental gradients