Physical and chemical consequences of artificially deepened thermocline in a small humic lake - a paired whole-lake climate change experiment

Peer reviewe

Large-scale long-term passive-acoustic monitoring reveals spatio-temporal activity patterns of boreal bats

The distribution ranges and spatio-temporal patterns in the occurrence and activity of boreal bats are yet largely unknown due to their cryptic lifestyle and lack of suitable and efficient study methods. We approached the issue by establishing a permanent passive-acoustic sampling setup spanning the area of Finland to gain an understanding on how latitude affects bat species composition and activity patterns in northern Europe. The recorded bat calls were semi-automatically identified for three target taxa; Myotis spp., Eptesicus nilssonii or Pipistrellus nathusii and the seasonal activity patterns were modeled for each taxa across the seven sampling years (2015-2021). We found an increase in activity since 2015 for E. nilssonii and Myotis spp. For E. nilssonii and Myotis spp. we found significant latitude -dependent seasonal activity patterns, where seasonal variation in patterns appeared stronger in the north. Over the years, activity of P. nathusii increased during activity peak in June and late season but decreased in mid season. We found the passive-acoustic monitoring network to be an effective and cost-efficient method for gathering bat activity data to analyze spatio-temporal patterns. Long-term data on the composition and dynamics of bat communities facilitates better estimates of abundances and population trend directions for conservation purposes and predicting the effects of climate change

Regional assessment of the current extent of acidification of surface waters in Europe and North America

The current status of surface water acidification related to air pollution in Europe and North America has been assessed using country reports, monitoring data, critical loads and exceedance data, acid sensitivity and deposition maps, and data reported under the European Commission’s Water Framework Directive (WFD). Acidification is still observed in many countries, but the extent and severity vary. Maps of acid sensitivity and deposition suggest that surface water acidification is present in regions and countries for which no data or reports were delivered for the current assessment. Existing national monitoring varies in the ability to assess the spatial extent of acidification and the recovery responses of acidified sites. The monitoring requirements under the European Union’s National Emission Ceilings Directive are expected to reverse the recent decline in the number of monitoring sites observed in some countries. The information reported under the WFD is currently of limited value in assessing the extent of acidification of surface waters in Europe. Chemical recovery in response to reductions in acid deposition can be slow, and biological recovery can lag severely behind. Despite large and effective efforts across Europe and North America to reduce surface water acidification, air pollution still constitutes a threat to freshwater ecosystems

Risk factors for moderate and severe persistent pain in patients undergoing total knee and hip arthroplasty : a prospective predictive study

Persistent post-surgical pain (PPSP) is a major clinical problem with significant individual, social and health care costs. The aim of this study was to examine the joint role of demographic, clinical and psychological risk factors in the development of moderate and severe PPSP after Total Knee and Hip Arthroplasty (TKA and THA, respectively). This was a prospective study wherein a consecutive sample of 92 patients were assessed 24 hours before (T1), 48 hours after (T2) and 4-6 months (T3) after surgery. Hierarchical logistic regression analyses were performed to identify predictors of moderate and severe levels of PPSP. Four to six months after TKA and THA, 54 patients (58.7%) reported none or mild pain (Numerical Rating Scale: NRS 3). In the final multivariate hierarchical logistic regression analyses, illness representations concerning the condition leading to surgery (osteoarthritis), such as a chronic timeline perception of the disease, emerged as a significant predictor of PPSP. Additionally, post-surgical anxiety also showed a predictive role in the development of PPSP. Pre-surgical pain was the most significant clinical predictive factor and, as expected, undergoing TKA was associated with greater odds of PPSP development than THA. The findings on PPSP predictors after major joint arthroplasties can guide clinical practice in terms of considering cognitive and emotional factors, together with clinical factors, in planning acute pain management before and after surgery.This work was supported by a Project grant (PTDC/SAU-NEU/108557/2008) and by a PhD grant (SFRH/BD/36368/2007) from the Portuguese Foundation of Science and Technology, COMPETE and FEDER. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Assessing ecological resilience to human induced environmental change in shallow lakes

Sudden unpredictable changes in ecosystems are an increasing source of concern because of their inherent unpredictability and the difficulties involved in restoration. Our understanding of the changes that occur across different trophic levels and the form of this change is lacking. This is especially true of large shallow lakes, where characteristics such as fetch and depth are close to theoretical boundary values for hysteretic behaviour. The development of reliable indicators capable of predicting these changes has been the focus of much research in recent years. The success of these early warning indicators (EWIs) has so far been mixed. There remain many unknowns about how they perform under a wide variety of conditions and parameters. Future climate change is predicted to have a wide range of impacts through the interaction of combined pressures, making the understanding of EWIs and the in-lake processes that occur during regime shifts imperative. Loch Leven, Scotland, UK, is a large shallow lake with a history of eutrophication, research and management and as such is an ideal study site to better understand resilience and regime shifts under a range of interacting stressors. The objectives of this research are to: (1) analyse long term data to identify the occurrence of common tipping points within the chemical (water column nutrient concentrations) and biological (macrophytes, phytoplankton, zooplankton) components of the loch, then test these tipping points using five statistical early warning indicators (EWIs) across multiple rolling window sizes; and (2) quantify the changes in lake ecology using a before/after analysis and testing for non-linearity, combined with modelling using the aquatic ecosystem process model PCLake to determine the level of resilience following a regime shift during recovery from eutrophication; (3) using PCLake, examine the sensitivity of Loch Leven to regime shifts in the face of predicted environmental change (e.g. climate change, nutrient pollution). Statistical analysis identified tipping points across all trophic levels included, from physical and chemical variables through to apex predators. The success of EWIs in predicting the tipping points was highly dependent on the number of EWIs used, with window size having a smaller impact. The 45% window size had the highest overall accuracy across all EWIs but only detected 16.5% more tipping points than the window size with the lowest overall accuracy. Differences between individual EWI performance and usage of them as a group was substantial with a 29.7% increase between the two. In both individual and group use of EWIs, false positives (early warning without a tipping point) were more common than true positives (tipping point preceded by EWI), creating significant doubts about their reliability as management tools. Significant change was seen across multiple variables and trophic levels in the before/after analysis following sudden recovery from eutrophication, with most variables also showing evidence of non-linear change. Modelling of responses to nutrient loading for chlorophyll, zooplankton and macrophytes, under states from before and after the shift, indicate hysteresis and thus the presence of feedback mechanisms. The modelling of responses to nutrient loading and predicted climate change in temperature and precipitation demonstrated that increases in temperature and decreases in summer precipitation individually had large impacts on chlorophyll and zooplankton at medium to high phosphorus (P) loads. However, modelling of the combined effects of these changes resulted in the highest lake chlorophyll concentrations of all tested scenarios. At low P loads higher temperatures and increased winter precipitation had the greatest impact on system resilience with a lower Critical Nutrient Load (CNL). The difference between chlorophyll and zooplankton as opposed to macrophytes was in the presence of a lower CNL for the increased winter precipitation-only scenarios which was not seen in the macrophytes. This highlights the potential role of high winter inputs potentially loaded with particulate matter in reducing resilience at lower P loads. This research has highlighted the vulnerability and low resilience of Loch Leven to environmental change. The presence of multiple tipping points and high levels of EWI activity show a high level of flexibility in the system. Coupled with the occurrence of widespread trophic change during a sudden recovery and a small level of hysteresis and high levels of sensitivity to climate change, the low levels of resilience become clear. The impact of lake-specific characteristics such as moderate depth, large fetch and a heterogeneous bed morphology is particularly evident in the limitations on macrophyte cover and the reliance on zooplankton to determine the hysteresis offset (amount of phosphorus (P) loading between the two CNL). The presence of these characteristics can be used to identify other lakes vulnerable to change. Improving the predictive capabilities of resilience indicators such as EWIs, and better understanding of the ecological changes that occur during non-linear change in response to recovery and climate change, can help target relevant ecosystem components for preventative management. These actions may become necessary under even the most conservative estimates of environmental change

Sequential patterns in social interaction states for regulation in collaborative learning

Abstract This study explored sequential patterns in social interaction states for group-level regulation of learning during collaborative learning. The participants were secondary school students (N = 92) performing collaborative physics tasks. The videotaped sessions were analyzed regarding participation, social interaction, and group-level regulation types of co- and socially shared regulation. The results show that group-level regulation emerged most frequently in social interaction state that included cognitive and socioemotional interaction and whole-group participation, which also led to and followed regulation most frequently. The findings highlight the role of joint participation in social interactions for regulation of learning in collaborative group settings

Predicting regulatory activities for socially shared regulation to optimize collaborative learning

Abstract This study utilized multimodal learning analytics and AI-based methods to examine the patterns of the socially shared regulation of collaborative learning (CL). The study involved multimodal data involving video and electrodermal activities (EDA) data collected from ninety-four secondary school students (N = 94) during five science lessons to reveal trigger events in CL. A novel concept of trigger events is introduced, which are challenging events and/or situations that may inhibit collaboration and will, therefore, require strategic adaptation in the regulation of cognition, motivation, and emotion within the group. The ANOVA results for the Skin Conductance Responses (SCRs) analysis indicated the disparity of physiological behavior activated in relation to different types of interactions for regulation. Process analysis and episode-rule mining were applied to reveal regulatory patterns in CL, while an AI approach with long short-term memory (LSTM) deep-learning networks were designed for pattern prediction. LSTM has emerged as the most widely applied artificial recurrent neural network (RNN) architecture for sequential data analysis and classification. The proposed AI network holds the potential for designing solutions for similar signal-processing problems in studying learning regulation. This study contributes to developing AI-enabled real-time support for regulation in collaborative learning

Relationship between critical load exceedances and empirical impact indicators at Integrated Monitoring sites across Europe

Critical loads for acidification and eutrophication and their exceedances were determined for a selection of ecosystem effects monitoring sites in the Integrated Monitoring programme (UNECE ICP IM). The level of protection of these sites with respect to acidifying and eutrophying deposition was estimated for 2000 and 2020. In 2020 more sites were protected from acidification (67%) than in 2000 (61%). However, due to the sensitivity of the sites, even the maximum technically feasible emission reductions scenario would not protect all sites from acidification. In 2000, around 20% of the IM sites were protected from eutrophication. In 2020, under reductions in accordance with current legislation, about one third of the sites would be protected, and at best, with the maximum technically feasible reductions, half of the sites would be protected from eutrophication. Data from intensively monitored sites, such as those in ICP IM, provide a connection between modelled critical thresholds and empirical observations, and thus an indication of the applicability of critical load estimates for natural ecosystems. Across the sites, there was good correlation between the exceedance of critical loads for acidification and key acidification parameters in runoff water, both with annual mean fluxes and concentrations. There was also evidence of a link between exceedances of critical loads of nutrient nitrogen and nitrogen leaching. The collected empirical data of the ICP IM thus allow testing and validation of key concepts used in the critical load calculations. This increases confidence in the European-scale critical loads mapping used in integrated assessment modelling to support emission reduction agreements