Whereas there is evidence that mixed-species approaches to production forestry in general can provide positive outcomes relative to monocultures, it is less clear to what extent multiple benefits can be derived from specific mixed-species alternatives. To provide such insights requires evaluations of an encompassing suite of ecosystem services, biodiversity, and forest management considerations provided by specific mixtures and monocultures within a region. Here, we conduct such an assessment in Sweden by contrasting even-aged Norway spruce (Piceaabies)-dominated stands, with mixed-species stands of spruce and birch (Betula pendula or B. pubescens), or spruce and Scots pine (Pinussylvestris). By synthesizing the available evidence, we identify positive outcomes from mixtures including increased biodiversity, water quality, esthetic and recreational values, as well as reduced stand vulnerability to pest and pathogen damage. However, some uncertainties and risks were projected to increase, highlighting the importance of conducting comprehensive interdisciplinary evaluations when assessing the pros and cons of mixtures.

The topic of shedding of micro-sized polymeric particles, so called microplastics, from textiles has been covered by an increasing number of studies over the past years. However, the methods with which the shedding of microplastics from textiles has been measured so far has shown a large variation. Consequently, the results regarding the amount of shed particles also vary, from 120 to 728,289 particles from similar garments in recent studies. This article presents research enabling for identification of whether the shedding of microplastics from different types of fabric was dependent on construction parameters. As none of the methods in the existing literature could be used for evaluating shedding of microplastics from textiles, a method was developed for this purpose. The resulting final method is described in this paper as well as the work with minimizing the error sources and consequently the standard deviation of the results through selection of material samples, equipment and procedure for sample preparation, washing, filtering the washing water and analyzing the shed microplastics. Comparing the environmental load of different garments, or identifying improvement possibilities in garment construction are two examples of how the method can be utilized.

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Background The increasing availability of remotely sensed data has recently challenged the traditional way of performing forest inventories, and induced an interest in model-based inference. Like traditional design-based inference, model-based inference allows for regional estimates of totals and means, but in addition for wall-to-wall mapping of forest characteristics. Recently Light Detection and Ranging (LiDAR)-based maps of forest attributes have been developed in many countries and been well received by users due to their accurate spatial representation of forest resources. However, the correspondence between such mapping and model-based inference is seldom appreciated. In this study we applied hierarchical model-based inference to produce aboveground biomass maps as well as maps of the corresponding prediction uncertainties with the same spatial resolution. Further, an estimator of mean biomass at regional level, and its uncertainty, was developed to demonstrate how mapping and regional level assessment can be combined within the framework of model-based inference. Results Through a new version of hierarchical model-based estimation, allowing models to be nonlinear, we accounted for uncertainties in both the individual tree-level biomass models and the models linking plot level biomass predictions with LiDAR metrics. In a 5005 km2 large study area in south-central Sweden the predicted aboveground biomass at the level of 18 m ×18 m map units was found to range between 9 and 447 Mg ·ha−1. The corresponding root mean square errors ranged between 10 and 162 Mg ·ha−1. For the entire study region, the mean aboveground biomass was 55 Mg ·ha−1 and the corresponding relative root mean square error 8%. At this level 75% of the mean square error was due to the uncertainty associated with tree-level models. Conclusions Through the proposed method it is possible to link mapping and estimation within the framework of model-based inference. Uncertainties in both tree-level biomass models and models linking plot level biomass with LiDAR data are accounted for, both for the uncertainty maps and the overall estimates. The development of hierarchical model-based inference to handle nonlinear models was an important prerequisite for the study.

Diet quality is an important determinant of animal survival and reproduction, and can be described as the combination of different food items ingested, and their nutritional composition. For large herbivores, human landscape modifications to vegetation can limit such diet-mixing opportunities. Here we use southern Sweden's modified landscapes to assess winter diet mixtures (as an indicator of quality) and food availability as drivers of body mass (BM) variation in wild moose (Alces alces). We identify plant species found in the rumen of 323 moose harvested in Oct-Feb, and link variation in average calf BM among populations to diets and food availability. Our results show that variation in calf BM correlates with variation in diet composition, diversity, and food availability. A varied diet relatively rich in broadleaves was associated with higher calf BM than a less variable diet dominated by conifers. A diet high in shrubs and sugar/starch rich agricultural crops was associated with intermediate BM. The proportion of young production forest (0-15 yrs) in the landscape, an indicator of food availability, significantly accounted for variation in calf BM. Our findings emphasize the importance of not only diet composition and forage quantity, but also variability in the diets of large free-ranging herbivores. Eating is complicated. Animals have to trade off a food item's potential energetic and nutritional gains against the risks of acquisition, such as the increased vulnerability to predation, exposure to plant toxins, or conspecific antagonism 1. What an individual eats, and where and when it does so, will in turn affect its fitness 2,3 , as diet quality is an important determinant of reproduction and survival in animal populations 4. For cervids (members of the deer family Cervidae), diet has repeatedly been shown to influence physiological and reproductive fitness 5-7. The impact of diet on individual fitness can occur through changes in body mass (BM), as well as through maternal nutritional effects 8,9 that can have flow-on implications for several generations 10. Diet quality is primarily determined by the combination of different plant items ingested, and each item's nutritional composition 11. A high diversity of available food items should enable a balanced intake of nutrients and energy 11 , and the avoidance of high doses of each plant species' defensive chemicals 12. Globally, intensive land management practices are altering an increasing proportion of land area 13,14. This can cause food resources to become concentrated in space and time 15 , and constrain the ability of cervids to acquire a suitable diet. Even in sparsely inhabited northern Europe, human modification of the landscape has been extensive 16 , with some regions primarily defined by intensive forestry, agriculture, urban environments, and limited protected areas. Humans largely control both the cervids' food resources and mortality rates. In many regions, this has led to an increase in some cervid populations 17. Furthermore, in these env...