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1. Animal migration is one of the most spectacular and visible behavioural phenomena in nature with profound implications for a range of ecological and evolutionary processes. Successful migration hinges on the ability to exploit temporary resources (e.g. food) and evade threats (e.g. predators) as they arise, and thus the timing of migration is often regarded as a dominant predictor of individual migratory success. 2. However, with the exception of intensively studied taxa (mainly birds), relatively few studies have investigated inter-individual annual and seasonal variation in migratory timing and performance, or tested predictions on how migration across high and low predation-risk habitats may exert selection on migratory timing. In particular, studies that assess the survival consequences of variation in migratory timing remain rare, which is most likely due to the logistical challenges associated with monitoring survival success and population-level characteristics simultaneously. 3. Here, we address the above-mentioned questions using roach Rutilus rutilus, a fish that migrates from lakes characterised by high predation risk into low-risk streams during winter. Specifically, we used individual-based tracking of roach in two European lake systems over multiple migration periods (9 and 7 years respectively), to obtain highly detailed (year-round scheduling, repeat journeys and the fate of individuals) data on the variability/synchrony of migratory timing in spring and autumn respectively. 4. We report seasonal differences in the variability of migratory timing, with lower variance and higher migration synchrony in spring lake arrival timing as compared to autumn lake departure timing. Furthermore, the timing of autumn migration is more variable across years than the timing of spring migration. Second, we find that later arrival to the lake habitat is positively associated with apparent survival from 1 year to the next, whereas we found no effect of lake departure timing on survival probability. 5. These findings represent rare evidence showing how intraspecific variation in timing in migratory fish differs across years and seasons, and how variation in timing can translate into survival consequences for prey in systems characterised by high predation risk.

Climate change mitigation trade-offs between increasing harvests to exploit substitution effects versus accumulating forest carbon sequestration complicate recommendations for climate beneficial forest management. Here, a time dynamic assessment ascertains climate change mitigation potential from different rotation forest management alternatives across three Swedish regions integrating the forest decision support system Heureka RegWise with a wood product model using life cycle assessment data. The objective is to increase understanding on the climate effects of varying the forest management. Across all regions, prolonging rotations by 20% leads on average to the largest additional net climate benefit until 2050 in both, saved emissions and temperature cooling, while decreasing harvests by 20% leads to the cumulatively largest net climate benefits past 2050. In contrast, increasing harvests or decreasing the rotation period accordingly provokes temporally alternating net emissions, or slight net emission, respectively, regardless of a changing market displacement factor. However, future forest calamities might compromise potential additional temperature cooling from forests, while substitution effects, despite probable prospective decreases, require additional thorough and time explicit assessments, to provide more robust policy consultation.

The evolution of multicellular life has played a pivotal role in shaping biological diversity. However, we know surprisingly little about the natural environmental conditions that favour the formation of multicellular groups. Here we experimentally examine how key environmental factors (predation, nitrogen and water turbulence) combine to influence multicellular group formation in 35 wild unicellular green algae strains (19 Chlorophyta species). All environmental factors induced the formation of multicellular groups (more than four cells), but there was no evidence this was adaptive, as multicellularity (% cells in groups) was not related to population growth rate under any condition. Instead, population growth was related to extracellular matrix (ECM) around single cells and palmelloid formation, a unicellular life-cycle stage where two to four cells are retained within a mother-cell wall after mitosis. ECM production increased with nitrogen levels resulting in more cells being in palmelloids and higher rates of multicellular group formation. Examining the distribution of 332 algae species across 478 lakes monitored over 55 years, showed that ECM and nitrogen availability also predicted patterns of obligate multicellularity in nature. Our results highlight that adaptations of unicellular organisms to cope with environmental challenges may be key to understanding evolutionary routes to multicellular life.

Mean square error optimal estimation requires the full correlation structure to be available. Unfortunately, it is not always possible to maintain full knowledge about the correlations. One example is decentralized data fusion where the cross-correlations between estimates are unknown, partly due to information sharing. To avoid underestimating the covariance of an estimate in such situations, conservative estimation is one option. In this paper the conservative linear unbiased estimator is formalized including optimality criteria. Fundamental bounds of the optimal conservative linear unbiased estimator are derived. A main contribution is a general approach for computing the proposed estimator based on robust optimization. Furthermore, it is shown that several existing estimation algorithms are special cases of the optimal conservative linear unbiased estimator. An evaluation verifies the theoretical considerations and shows that the optimization based approach performs better than existing conservative estimation methods in certain cases. Funding Agencies|Center for Industrial Information Technology at Linkoping University [17.12]; Industry Excellence Center LINK-SIC - Swedish Governmental Agency for Innovation Systems; Saab AB; Project Scalable Kalman filters - Swedish Research Council

Research on diel vertical migration (DVM) is generally conducted at the population level, whereas few studies have focused on how individual animals behaviorally respond to threats when also having access to foraging opportunities. We utilized a 3D tracking platform to record the swimming behavior of Daphnia magna exposed to ultraviolet radiation (UVR) in the presence or absence of a food patch. We analyzed the vertical position of individuals before and during UVR exposure and found that the presence of food reduced the average swimming depth during both sections of the trial. Since UVR is a strong driver of zooplankton behavior, our results highlight that biotic factors, such as food patches, have profound effects on both the amplitude and the frequency of avoidance behavior. In a broader context, the trade‐off between threats and food adds to our understanding of the strength and variance of behavioral responses to threats, including DVM., Research on individual behavior in zooplankton, a globally important group of organisms, is lacking. We used 3D tracking of individual water fleas to test how the response to threats is modified by foraging opportunities. In the presence of food, threat response is reduced.

The forest sector can play a pivotal role in mitigating climate warming by decreasing emissions to the atmosphere and increasing carbon removals. In an expanding bioeconomy, the pulp and paper industry provides opportunities for various low-carbon wood products with promising substitution effects. However, assessing climate effects of wood product systems is complex and requires a holistic approach. The objective of this study was to advance time dynamic climate impact assessment of a bioeconomically promising wood product from a system perspective. For this purpose, a time dynamic life cycle assessment was conducted on a pulp-based beverage carton. The assessment included fossil value chain emissions from cradle to grave, effects from biogenic carbon in a eucalyptus plantation, and credits from substitution. A polyethylene terephthalate (PET) bottle was considered for material substitution (MS) and differing marginal electricity and heat mixes for energy substitution. The results revealed dominating climate warming from value chain emissions and slight offsetting by biogenic carbon from standing biomass and soil organic carbon, and short-term carbon storage in the beverage carton. MS and displacing marginal energy mixes transformed the climate warming into a substantial total cooling effect. However, substitution effects varied strongly in terms of substitution factors and temperature change with varying replacement rate of the beverage carton and different marginal energy mixes. A climate cooling range of -0.8 center dot 10(-15) to -1.8 center dot 10(-15) K per unit of beverage carton by 2050 was found, highlighting potential relevance for climate policy making. Thus, production and use of wood-based beverage cartons over PET bottles can have climate cooling effects. Further assessments on alternative forestry systems (e.g., Nordic forests) are needed to identify the role of biogenic carbon in holistic climate assessments, with dynamic substitution effects included to increase the validity.

In this paper, we propose a distributed second-order augmented Lagrangian method for distributed optimal control problems, which can be exploited for distributed model predictive control. We employ a primal-dual interior-point approach for the inner iteration of the augmented Lagrangian and distribute the corresponding computations using message passing over what is known as the clique tree of the problem. The algorithm converges to its centralized counterpart and it requires fewer communications between sub-systems as compared to algorithms such as the alternating direction method of multipliers. We illustrate the efficiency of the framework when applied to randomly generated interconnected sub-systems as well as to a vehicle platooning problem. Funding: Wallenberg AI, Autonomous Systems and Software Program (WASP) - Knut and Alice Wallenberg Foundation

Recent land-use changes have led to a significant loss of natural wetlands worldwide resulting in increased amounts of organic and inorganic compounds reaching lakes and coastal areas. In turn, this has led to an increased algal growth, and subsequently the risk of algal blooms and deteriorated water quality. The capacity of wetlands to retain nutrients is well-known, suggesting that constructed wetlands may be a potential management strategy to mitigate algal blooms in downstream waters, although little is known about seasonal variation in reduction of algal growth potential. Therefore, in a long-term study, we experimentally evaluated the efficiency of seven wetlands to reduce the algal growth potential by comparing the growth in cultures containing 50:50 wetland water from the inlet or outlet and water from a eutrophic lake as a standard inoculum. We show that the majority of the wetlands have a considerable potential to reduce algal growth potential, with up to 89% for cyanobacteria and 73% for green algae. However, there were strong temporal variations in efficiency within, as well as between wetlands. Specifically, we show that the potential to reduce algal growth (standardized conditions) was generally higher in winter than in summer. In addition, the wetlands showed different efficiency in reducing the growth potential of cyanobacteria and green algae. Taken together, our results show that wetlands have a considerable potential to reduce algal growth potential, suggesting that they are an efficient local-scale tool in reducing the risk of algal blooms especially from a future climate change perspective.

Lane-level map matching is essential for autonomous driving. In this paper, we propose a Hidden Markov Model (HMM) for matching a trajectory of noisy GPS measurements to the road lanes in which the vehicle records its positions. To our knowledge, this is the first time that HMM is used for lane-level map matching. Apart from GPS values, the model is further assisted by yaw rate data (converted to a lane change indicator signal) and visual cues in the form of the left and right lane marking types (dashed, solid, etc.). Having defined expressions for the HMM emission and transition probabilities, we evaluate our model to demonstrate that it achieves 95.1% recall and 3.3% median path length error for motorway trajectories.

As the use of engineered nanomaterials increases, so does the risk of them spreading to natural ecosystems. Hitherto, knowledge regarding the toxic properties of nanoparticles (NP’s) and their potential interactions with natural bio-organic molecules adsorbed to them, and thereby forming surface coronas, is limited. However, we show here that the toxic effect of NPs of tungsten carbide cobalt (WC–Co) and cobalt (Co) on the crustacean Daphnia magna is postponed in the presence of natural biological degradation products (eco-corona biomolecules). For Daphnia exposed to WC–Co NPs the survival time increased with 20–25% and for Co NPs with 30–47% after mixing the particles with a solution of eco-corona biomolecules before exposure. This suggests that an eco-corona, composed of biomolecules always present in natural ecosystems, reduces the toxic potency of both studied NPs. Further, the eco-coronas did not affect the particle uptake, suggesting that the reduction in toxicity was related to the particle-organism interaction after eco-corona formation. In a broader context, this implies that although the increasing use and production of NPs may constitute a novel, global environmental threat, the acute toxicity and long-term effects of some NPs will, at least under certain conditions, be reduced as they enter natural ecosystems.

Bioenergy with carbon capture and storage (BECCS) plays a central role in scenario pathways that limit global warming in line with the objectives of the Paris Agreement. Yet deliberate policy efforts to incentivise BECCS—whether through amending existing climate policies or introducing entirely new ones—remain rare. In this paper, we contend that BECCS must be incentivised responsibly, through policy-making processes which account for diverse and geographically varying societal values and interests. More specifically, we make the case for responsible incentivisation by undertaking a comparative analysis of stakeholder attitudes to four idealised policy scenarios for BECCS, including representatives of government, business, nongovernmental and academic communities, in the UK and Sweden. The scenarios were: business as usual; international policy reform; national BECCS policy; and national policy for negative emissions technologies. Based on our findings, we recommend that policymakers 1) recognise the need to develop new incentives and make enabling reforms to existing policy instruments; 2) consider the risk of mitigation deterrence in their real world (and not abstracted) contexts; 3) employ multi-instrument approaches to incentivisation that do not overly rely on carbon pricing or 4) force a choice between technology specific or technology neutral policies; and 5) attend to the diversity of stakeholder and wider public perspectives that will ultimately determine the success—or failure—of their policy designs.

An individual's phenotype can be altered by direct contact with its present environment but also by environmental features experienced by previous generations, that is, parental or grandparental effects. However, the strength and direction of these transgenerational effects may be highly variable according to the ecological conditions experienced by ancestral generations. Here, we performed a reciprocal split-brood experiment to compare transgenerational responses to the threat of ultraviolet radiation (UVR) in the zooplankter Daphnia magna, which had, or had not, been exposed to UVR for more than 150 generations. We found that the environment at which parents and grandparents were reared significantly influenced both behavior and life-history traits of their descendants. However, such transgenerational responses differed between D. magna individuals with contrasting ancestral stress history, that is, when exposed to UVR previously unexposed individuals rapidly changed their behavior and life-history traits, whereas individuals previously exposed to UVR showed less pronounced response when the UVR threat level relaxed. Hence, we here demonstrate an asymmetric transgenerational plasticity in response to UVR threat. The findings advance our understanding on the evolutionary ecology of such transgenerational effects and their potential role in response to changes in the local environment.

In this paper we present a distributed second-order augmented Lagrangian method for distributed model predictive control. We distribute the computations for search direction, step size, and termination criteria over what is known as the clique tree of the problem and calculate each of them using message passing. The algorithm converges to its centralized counterpart and it requires fewer communications between sub-systems as compared to algorithms such as the alternating direction method of multipliers. Results from a simulation study confirm the efficiency of the framework.

One of the main aspects of switched affine systems that makes their stabilizability study intricate is the existence of (generally) infinitely many attainable equilibrium points in the state space. Thus, prior to designing the switched control, the user must specify one of these equilibrium points to be the goal or reference. This can be a cumbersome task, especially if this goal is partially given or only defined as a set of constraints. To tackle this issue, in this paper we describe algorithms that can determine whether a given goal is an equilibrium point of the system and also jointly search for equilibrium points and design stabilizing switching functions.

Food waste is a significant problem within public catering establishments, caused mainly by serving waste arising from overcatering. Overcatering means that public catering establishments rarely run out of food but surplus ends up as food waste. The challenge is to find a solution that minimizes food waste while ensuring that sufficient food can be provided. A key element in this balancing act is to forecast accurately the number of meals needed and cook that amount. This study examined conventional forecasting methods (last-value forecasting, moving-average models) and more complex models (prophet model, neural network model) and calculated associated margins for all models. The best-performing model for each catering establishment was then used to evaluate the optimal number of portions based on stochastic inventory theory. Data used in the forecasting models are number of portions registered at 21 schools in the period 2010–2019. The past year was used for testing the models against real observations. The current business as usual scenario results in a mean average percentage error of 20–40%, whereas the best forecasting case around 2–3%. Irrespective of forecasting method, meal planning needed some safety margin in place for days when demand exceeded the forecast level. Conventional forecasting methods were simple to use and provided the best results in seven cases, but the neural network model performed best for 11 out of 21 kitchens studied. Forecasting can be one option on the road to achieve a more sustainable public catering sector.

In this study, Life Cycle Assessment (LCA) methodology was combined with the agro-ecosystem model DNDC to assess the climate and eutrophication impacts of perennial grass cultivation at five different sites in Sweden. The system was evaluated for two fertilisation rates, 140 and 200 kg N ha(-1). The climate impact showed large variation between the investigated sites. The largest contribution to the climate impact was through soil N2O emissions and emissions associated with mineral fertiliser manufacturing. The highest climate impact was predicted for the site with the highest clay and initial organic carbon content, while lower impacts were predicted for the sandy loam soils, due to low N2O emissions, and for the silty clay loam, due to high carbon sequestration rate. The highest eutrophication potential was estimated for the sandy loam soils, while the sites with finer soil texture had lower eutrophication potential. According to the results, soil properties and weather conditions were more important than fertilisation rate for the climate impact of the system assessed. It was concluded that agro-ecosystem models can add a spatial and temporal dimension to environmental impact assessment in agricultural LCA studies. The results could be used to assist policymakers in optimising use of agricultural land.

The operation of power-to-X systems requires measures to control the cost and sustainability of electricity purchased from spot markets. This study investigated different bidding strategies for the day-ahead market with a special focus on Sweden. A price independent order (PIO) strategy was developed assisted by forecasting electricity prices with an artificial neural network. For comparison, a price dependent order (PDO) with fixed bid price was used. The bidding strategies were used to simulate H2 production with both alkaline and proton exchange membrane electrolysers in different years and technological scenarios. Results showed that using PIO to control H2 production helped to avoid the purchase of expensive and carbon intense electricity during peak loads, but it also reduced the total number of operating hours compared to PDO. For this reason, under optimal conditions for both bidding strategies, PDO resulted in an average of 10.9% lower levelised cost of H2, and more attractive cash flows and net present values than PIO. Nevertheless, PIO showed to be a useful strategy to control costs in years with unexpected hourly price behaviour such as 2018. Furthermore, PIO could be successfully demonstrated in a practical case study to fulfil the on-demand requirement of an industrial captive customer.

Albedo change during feedstock production can substantially alter the life cycle climate impact of bioenergy. Life cycle assessment (LCA) studies have compared the effects of albedo and greenhouse gases (GHGs) based on global warming potential (GWP). However, using GWP leads to unequal weighting of climate forcers that act on different timescales. In this study, albedo was included in the time-dependent LCA, which accounts for the timing of emissions and their impacts. We employed field-measured albedo and life cycle emissions data along with time-dependent models of radiative transfer, biogenic carbon fluxes and nitrous oxide emissions from soil. Climate impacts were expressed as global mean surface temperature change over time ( increment T) and as GWP. The bioenergy system analysed was heat and power production from short-rotation willow grown on former fallow land in Sweden. We found a net cooling effect in terms of increment T per hectare (-3.8 x 10(-11) K in year 100) and GWP(100) per MJ fuel (-12.2 g CO(2)e), as a result of soil carbon sequestration via high inputs of carbon from willow roots and litter. Albedo was higher under willow than fallow, contributing to the cooling effect and accounting for 34% of GWP(100), 36% of increment T in year 50 and 6% of increment T in year 100. Albedo dominated the short-term temperature response (10-20 years) but became, in relative terms, less important over time, owing to accumulation of soil carbon under sustained production and the longer perturbation lifetime of GHGs. The timing of impacts was explicit with increment T, which improves the relevance of LCA results to climate targets. Our method can be used to quantify the first-order radiative effect of albedo change on the global climate and relate it to the climate impact of GHG emissions in LCA of bioenergy, alternative energy sources or land uses.

PIT-tagging is commonly used in behavioural studies of fish, although long-term evaluations of effects from tagging under natural conditions are scarce. We PIT-tagged common bream Abramis brama, European perch Perca fluviatilis, pike Esox lucius and roach Rutilus rutilus, released them in their lakes of origin and recaptured them after 103-3269 days. Overall, tagged fish did not differ in condition from non-tagged fish, except for small R. rutilus that weighed less in one lake in one year. We conclude that PIT-tagging in general has negligible long-term effects on fish condition. This article is protected by copyright. All rights reserved.

ObjectivesAdequate health literacy is important for patients to manage chronic diseases and medications. We examined the association between health literacy and multiple medications in community-dwelling adults aged 50 years and older in England.Design, settings and participantsWe included 6368 community-dwelling people of median age 66 years from the English Longitudinal Study of Ageing. Health literacy was assessed at wave 5 (2010/11) with 4 questions concerning a medication label. Four correct answers were categorised as adequate health literacy, otherwise low. Data on medications were collected at wave 6 (2012/13). To examine the difference in the number of medications between low and adequate health literacy, we used zero-inflated negative binomial regression, estimating odds ratio (OR) for zero medication and incidence rate ratios (IRR) for the number of medications, with 95% CIs. Associations were adjusted for demographic, socioeconomic and health characteristics, smoking and cognitive function. We also stratified the analysis by sex, and age (50–64 and ≥65 years). To be comparable with preceding studies, multinomial regression was fitted using commonly used thresholds of polypharmacy (0 vs 1–4, 5–9, ≥10 medications).ResultsAlthough low health literacy was associated with a lower likelihood of being medication-free (OR=0.64, 95% CI: 0.45 to 0.91), health literacy was not associated with the number of medications among those at risk for medication (IRR=1.01, 95% CI: 0.96 to 1.05), and this finding did not differ among younger and older age groups or women. Among men, low health literacy showed a weak association (IRR=1.06, 95% CI: 0.99 to 1.14). Multinomial regression models showed graded risks of polypharmacy for low health literacy.ConclusionsAlthough there was no overall association between health literacy and the number of medications, this study does not support the assertion that low health literacy is associated with a notably higher number of medications in men.

Biochar-producing cookstoves can supply fuel-efficient heat for cooking in developing countries. The produced biochar can be used as a soil amendment, providing a range of environmental and agronomic benefits and serve to remove carbon dioxide from the atmosphere. Despite these advantages, many stove initiatives have not been sustained in the long term, but very little attention has been devoted to understanding the reasons behind this. The present study contributes to filling this knowledge gap, by identifying key factors affecting the level of stove adoption and use, as well as biochar utilization. Based on a follow-up survey of 50 households in northwestern Tanzania that received microgasifier stoves in 2015, only 12 still made use of their stove 5 years later. One of the main reasons for this relates to the inadequate quality of stove material. Declining or inconsistent availability of feedstocks was also identified as a major challenge. Furthermore, the households generally did not embrace the idea of amending soils with biochar, due to a combination of local practices and perceptions, and a lack of education and awareness programs. We conclude that, under the conditions of the studied project, three factors are required to scale dissemination: improvement of the stove design, provision of training programs on biochar management and subsidies or microloans that would make more durable stoves affordable. Sustained stove deployment can only be achievable by institutionalizing financing structures that are independent from short-term grant-based initiatives. Funding: Swedish Research Council for Sustainable Development (Formas) within the National Research Programme on Climate "Visions and Conditions for a Fossil-Free Welfare Society" [2019-01973]; Swedish Research Council (VR) through the Swedish Government [2016-06359]; Sida through the Swedish Government [2016-06359] LUNETs

Agricultural land use and management affect land surface albedo and thus the climate. Increasing the albedo of cropland could enhance reflection of solar radiation, counteracting the radiative forcing (RF) of greenhouse gases (GHGs) and local warming. However, knowledge is lacking on how agricultural practices affect albedo under local conditions, and on the benefits of individual practices. In this study, field measurements were made in 15 paired plots at a site in Northern Europe to determine albedo, net shortwave irradiance and RF impacts under various common crops, cultivation intensities and tillage practices. Field data for 2019-2020 were compared with satellite-based albedo for the surrounding region in 2010-2020. At regional level, different combinations of soil type, yearly weather and agricultural practices led to great variability in the albedo of individual crops, despite similar pedo-climatic conditions. At field level within years, albedo differences were determined mainly by crop type, species-specific phenology and post-harvest management. Annual albedo was higher with perennial ley (0.20-0.22) and winter-sown crops (0.18-0.22) than with spring-sown crops (0.16-0.18) and bare soil (0.13). Barley had the highest albedo among winter and spring cereals. In summer, when increased albedo could alleviate local heat stress, oats reduced net shortwave irradiance at the surface by 0.8-5.8 Wm(-2) compared with other cereals, ley, peas or rapeseed. Delayed or reduced tillage gave high local cooling potential (up to-13.6 Wm(-2)) in late summer. Potential benefits for global mean climate as GWP(100 )per hectare and year reached-980 kg CO(2)e for avoiding black fallow,-578 kg CO(2)e for growing a winter-sown variety and-288 kg CO(2)e for delayed tillage. Thus realistic albedo increases on cropland could have important effects on local temperatures and offset a substantial proportion of the RF deriving from field-scale GHG emissions on short time-scales.