Using multi-source data to map and model the predisposition of forests to wind disturbance

Natural disturbances such as wind are known to cause threats to ecosystem services as well as sustainable forest ecosystem management. The objective of this research was to better understand and quantify drivers of predisposition to wind disturbance, and to model and map the probability of wind-induced forest disturbances (P_DIS) in order to support forest management planning. To accomplish this, we used open-access airborne light detection and ranging (LiDAR) data as well as multi-source National Forest Inventory (NFI) data to model P_DIS in southern Finland. A strong winter storm occurred in the study area in December 2011. High spatial resolution aerial images, acquired after the disturbance event, were used as reference data. Potential drivers associated with P_DIS were examined using a multivariate logistic regression model. The model based on LiDAR provided good agreement with detected areas susceptible to wind disturbance (73%); however, when LiDAR was combined with multi-source NFI data, the results were more promising: prediction accuracy increased to 81%. The strongest predictors in the model were mean canopy height, mean elevation, and stem volume of the main tree species (Norway spruce and Scots pine). Our results indicate that open-access LiDAR data can be used to model and map the probability of predisposition to wind disturbance, providing spatially detailed, valuable information for planning and mitigation purposes.     

Influence of fertilization, mulch color, early forcing, fruit order, planting date, shading, growing Environment, and genotype on the contents of selected phenolics in strawberry (Fragaria x ananassa Duch.) fruits

The influence of agricultural practices (fertilization, mulch color, early forcing, and planting date), environment (light and growing area), cultivar, and fruit order on the selected phenolic content and antioxidant activity in strawberry (Fragaria x ananassa Duch.) fruits was studied. Three different levels of fertilization were given to plants in the fertilization experiment. The lowest fertilization level increased the contents of flavonols and ellagic acid from 19 to 57%. Between cultivars, up to 4-fold differences were found in the flavonol content, and it also varied according to growing environment. Planting date in glasshouse production was important for the phenolic content, and a statistically significant interaction was found between planting date and fruit order. Fruit order caused at highest 1.5-2.0-fold differences in the contents of phenolics. Interestingly, compared with other phenolics, anthocyanins were affected differently by many factors. Thus, the findings show that minor cultivation changes can increase the content of phenolics, especially in under-glass production where conditions can be easily manipulated.     

Identification of boreal forest stands with high herbaceous plant diversity using airborne laser scanning

Boreal forest stands with high herbaceous plant species diversity have been found to be one of the main habitats for many endangered species, but the locations and sizes of these herb-rich forest stands are not well known in many areas. Better identification of the stands could improve both their conservation and management. A new approach is proposed here for locating the mature herb-rich forest stands using airborne laser scanner (ALS) data and logistic regression, or the k-NN classifier. We show that ALS technology is capable of distinguishing the ecologically important herb-rich forests from those growing on less fertile site types, mainly on the basis of unique but quantifiable crown structure and vertical profile that characterise forests on high fertility sites. The study site, Koli National Park, is located on the border of the southern and middle boreal vegetation zones in Finland, and includes 63 herb-rich forest stands of varying sizes. The model and test data comprised 274 forest stands belonging to five forest site types varying from very fertile to poor. The best overall classification accuracy achieved with the k-NN method was 88.9%, the herb-rich forests being classified correctly in 65.0% of cases and the other forest site types in 95.7%. The best overall classification accuracy achieved with logistic regression was 85.6%, being 55.0% for the herb-rich forests and 94.3% for the other forest site types. Both methods demonstrated promising potential for separating herb-rich forests from other forest site types, although slightly better results were obtained with the non-parametric k-NN method, which was capable of utilising a higher number of explanatory variables. It is concluded that ALS-based data analysis techniques are applicable to the detection of mature boreal herb-rich forests in large-scale forest inventories.     

Do environmental diversity approaches lead to improved site selection? A comparison with the multi-species approach

This paper suggests a new approach to select conservation areas cost-effectively according to the concept of complementarity and representation of focal natural features. The suggested environmental diversity (ED) site selection model maximizes ecological diversity, measured via ordination of the chosen taxa communities. Given their fundamental role in ecosystem functioning, vascular plants are chosen as the indicator taxa. We test the ED indicator model by contrasting it to the conventional site selection indicator (MS model), which maximizes the representation of species number in the indicator taxa. We demonstrate that the ED model is more cost-effective than the MS model. More importantly, while the ED selection is operative over the whole range of species, the MS selection does not work beyond the range of species, where all vascular plants become protected. Beyond that point MS indicator model cannot guide conservation efforts, which is a serious drawback. The ED model outperforms MS model also in terms of habitat conservation and taxonomic diversity. Thus, it provides an interesting selection framework for biodiversity.     

Vertical and horizontal distribution of ascending Atlantic salmon in power plant tailrace channels

Three‐dimensional distribution of adult upstream‐migrating Atlantic salmon, Salmo salar L., was studied in three power plant tailrace channels on the large, regulated River Kemijoki in northern Finland using novel pressure sensor radio telemetry. The salmon swam mostly at depths of 1–4 m below the surface, with the salmon‐specific averages ranging from 1.3 to 6.4 m. When approaching a power plant, no change in swimming depth was observed. The horizontal locations of salmon in the two regularly shaped tailrace channels peaked at 5–10 m distance from the shoreline and showed a positively skewed distribution with a tail towards the central part of the tailrace. A graphical presentation of salmon locations in the tailrace channel and data on swimming depth and distance from the shoreline may prove useful in determining the location and design of a fishway entrance and in dimensioning attraction flow.     

Seven distinct dietary patterns identified among pregnant Finnish women--associations with nutrient intake and sociodemographic factors

OBJECTIVES: To identify and describe dietary patterns in a cohort of pregnant women and investigate whether the dietary patterns are associated with dietary intake and sociodemographic factors. DESIGN: Mothers entering the Finnish Type 1 Diabetes Prediction and Prevention (DIPP) Nutrition Study in 1997-2002 were retrospectively asked to complete a food-frequency questionnaire concerning their diet during pregnancy. Principal components analysis was used to identify dietary patterns. SETTING: Finland. SUBJECTS: Subjects were 3730 women with a newborn infant carrying increased genetic susceptibility to type 1 diabetes mellitus. RESULTS: Seven factors were identified and named. Energy intake correlated positively with 'Healthy', 'Fast food', 'Traditional bread', 'Traditional meat' and 'Coffee' patterns and inversely with the 'Alcohol and butter' pattern. Intake of dietary fibre correlated positively with 'Healthy', 'Traditional bread' and 'Low-fat foods' patterns and inversely with the 'Alcohol and butter' pattern. The seven dietary patterns seemed to account for relatively large proportions of the variance in energy and nutrient intakes except for the intake of vitamin D, vitamin C, carotenoids and calcium. Maternal age and higher level of education were associated with higher scores on 'Healthy', 'Low-fat foods' and 'Alcohol and butter' patterns. CONCLUSION: Principal components analysis produced seven dietary patterns which may be useful for further research concerning maternal diet and health outcomes among both mothers and their offspring.     

Evolutionary impact assessment: accounting for evolutionary consequences of fishing in an ecosystem approach to fisheries management

Managing fisheries resources to maintain healthy ecosystems is one of the main goals of the ecosystem approach to fisheries (EAF). While a number of international treaties call for the implementation of EAF, there are still gaps in the underlying methodology. One aspect that has received substantial scientific attention recently is fisheries‐induced evolution (FIE). Increasing evidence indicates that intensive fishing has the potential to exert strong directional selection on life‐history traits, behaviour, physiology, and morphology of exploited fish. Of particular concern is that reversing evolutionary responses to fishing can be much more difficult than reversing demographic or phenotypically plastic responses. Furthermore, like climate change, multiple agents cause FIE, with effects accumulating over time. Consequently, FIE may alter the utility derived from fish stocks, which in turn can modify the monetary value living aquatic resources provide to society. Quantifying and predicting the evolutionary effects of fishing is therefore important for both ecological and economic reasons. An important reason this is not happening is the lack of an appropriate assessment framework. We therefore describe the evolutionary impact assessment (EvoIA) as a structured approach for assessing the evolutionary consequences of fishing and evaluating the predicted evolutionary outcomes of alternative management options. EvoIA can contribute to EAF by clarifying how evolution may alter stock properties and ecological relations, support the precautionary approach to fisheries management by addressing a previously overlooked source of uncertainty and risk, and thus contribute to sustainable fisheries.     

Carbon stock changes of forest land in Finland under different levels of wood use and climate change

Context

Prediction of the effect of harvests and climate change (CC) on the changes in carbon stock of forests is necessary both for CC mitigation and adaptation purposes.

Aims

We assessed the impact of roundwood and fuelwood removals and climate change (CC) on the changes in carbon stock of Finnish forests during 2007–2042. We considered three harvest scenarios: two based on the recent projections of roundwood and fuelwood demand, and the third reflecting the maximum sustainable cutting level. We applied two climate scenarios: the climate was in the state that prevailed around year 2006, or it changed according to the IPCC SRES A1B scenario.

Methods

We combined the large-scale forestry model MELA with the soil carbon model Yasso07 for mineral soils. For soils of drained, forested peatlands, we used a method based on emission factors.

Results

The stock change of trees accounted for approximately 80 % of the total stock change. Trees and mineral soils acted as carbon sinks and the drained peatland soils as a carbon source. The forest carbon sink increased clearly in both of the demand-based scenarios, reaching the level of 13–20 Tg C/year (without CC). The planned increase in the use of bioenergy reduced the forest sink by 2.6 Tg C/year. CC increased the forest carbon sink in 2042 by 38 %–58 % depending on the scenario. CC decreased the sink of mineral soils in the initial years of the simulations; after 2030, the effect was slightly positive. CC increased the emissions from the drained peatland soils.

Conclusions

It is likely that forest land in Finland acts as a carbon sink in the future. The changes in carbon stocks of trees, mineral soils, and peatland soils respond differently to CC and fuelwood and roundwood harvests.     

From a strategic to a tactical forest management plan using a hierarchic optimization approach

The Finnish state forest enterprise, Metsähallitus, defines the regional harvest levels for a 10-year period in a strategic-level natural resources plan. Although this plan defines stand-level harvest schedules for all stands, in practice, it cannot be used, as the harvests need to be clustered in time and in space. It is applied by giving each subregion goals they need to fulfill in a tactical level planning process, and the harvests are manually clustered into predefined groups of adjacent stands (departments). In this study, we developed a hierarchical optimization process making use of departments for clustering the harvests. For each of the departments, 91 different stand-level harvest schedules (plans) were determined using incomes from one period and the forest value at the end as objectives. The department-level plans were then used as alternatives in a region-level goal optimization problem. The resulting hierarchic plan was compared to the stand-level solution of the strategic-level plan which served as a benchmark plan. The hierarchical plan clustered the harvests and achieved the goals set better than the benchmark plan, but the net present income was 3.3% lower. The approach turned out usable, but further developing of the approach is needed to reduce the costs of clustering.