Interactive effects of multiple stressors vary with consumer interactions, stressor dynamics and magnitude

Predicting the impacts of multiple stressors is important for informing ecosystem management, but is impeded by a lack of a general framework for predicting whether stressors interact synergistically, additively, or antagonistically. Here we use process-based models to study how interactions generalise across three levels of bio-logical organisation (physiological, population, and community) for a simulated two-stressor experiment on a seagrass model system. We found that the same underlying processes could result in synergistic, additive or antagonistic interactions, with interaction type depending on initial conditions, experiment duration, stressor dynamics, and consumer presence. Our results help explain why meta-analyses of multiple stressor experimental results have struggled to identify predictors of consistently non-additive interactions in the natural environment. Experiments run over longer temporal scales, with treatments across gradients of stressor magnitude, are needed to identify the processes that underpin how stressors interact and provide useful predictions to management.

Human-machine-human interaction in motor control and rehabilitation: a review

Background Human-human (HH) interaction mediated by machines (e.g., robots or passive sensorized devices), which we call human-machine-human (HMH) interaction, has been studied with increasing interest in the last decade. The use of machines allows the implementation of different forms of audiovisual and/or physical interaction in dyadic tasks. HMH interaction between two partners can improve the dyad’s ability to accomplish a joint motor task (task performance) beyond either partner’s ability to perform the task solo. It can also be used to more efficiently train an individual to improve their solo task performance (individual motor learning). We review recent research on the impact of HMH interaction on task performance and individual motor learning in the context of motor control and rehabilitation, and we propose future research directions in this area. Methods A systematic search was performed on the Scopus, IEEE Xplore, and PubMed databases. The search query was designed to find studies that involve HMH interaction in motor control and rehabilitation settings. Studies that do not investigate the effect of changing the interaction conditions were filtered out. Thirty-one studies met our inclusion criteria and were used in the qualitative synthesis. Results Studies are analyzed based on their results related to the effects of interaction type (e.g., audiovisual communication and/or physical interaction), interaction mode (collaborative, cooperative, co-active, and competitive), and partner characteristics. Visuo-physical interaction generally results in better dyadic task performance than visual interaction alone. In cases where the physical interaction between humans is described by a spring, there are conflicting results as to the effect of the stiffness of the spring. In terms of partner characteristics, having a more skilled partner improves dyadic task performance more than having a less skilled partner. However, conflicting results were observed in terms of individual motor learning. Conclusions Although it is difficult to draw clear conclusions as to which interaction type, mode, or partner characteristic may lead to optimal task performance or individual motor learning, these results show the possibility for improved outcomes through HMH interaction. Future work that focuses on selecting the optimal personalized interaction conditions and exploring their impact on rehabilitation settings may facilitate the transition of HMH training protocols to clinical implementations.

The structure and robustness of tripartite ecological networks

ABSTRACTUntil recently, most ecological network analyses have focused on a single interaction type. In nature, however, diverse interactions co-occur, each of them forming a layer of a ‘multilayer’ network. Data including information on multiple interactions has recently started to emerge, giving us the opportunity to have a first glance at possible commonalities in the structure of these networks. We studied the structural features of 44 tripartite ecological networks from the literature, each composed of two layers of interactions (e.g. herbivory, parasitism, pollination), and investigated their fragility to species losses. We found that the way in which the different layers of interactions are connected to each other affect how perturbations spread in ecological communities. Our results highlight the importance of considering multiple interactions simultaneously to better gauge the robustness of ecological communities to species loss and to more reliably identify the species that are important for robustness.

The Biodiversity of Ecological Interactions: Challenges for recording and documenting the Web of Life

Biodiversity is more than a collection of individual species. It is the combination of biological entities and processes supporting life on Earth: no single species persists without interacting with other species. A full account of biodiversity on Earth needs to document the essential ecological interactions that support Earth’s system through their functional outcomes. Quantifying biodiversity’s interactome (the whole suite of interactions among biotic organisms) is challenging not just because of the daunting task of describing ecosystem complexity, it’s also limited by the need to define and establish a proper grammar to record and catalog species interactions. Actually, a record of a pairwise interaction between two species can be identified as a "tetranomial species", with just a concatenation of the two Latin binomials. Thus sampling interactions requires solving exactly the same constraints and problems we face when sampling biodiversity. In real interaction webs, the number of actual pairwise interactions among species in local assemblages scales exponentially with species richness. I discuss the main components of these interactions and those that are key to properly sample and document them. Interactions take the form of predation, competition, commensalism, amensalism, mutualism, symbiosis, and parasitism and, in all cases, involve reciprocal effects for the interacting species and build into highly complex networks (Fig. 1). The type of metadata required to document ecological interactions between partner species depends on interaction type; yet a fraction of these metadata is shared with those of the partner species. The interaction type sets limits to between-species encounters (actually, encounters between individuals of the partner species) and, more importantly, sets the type of outcome emerging from the interactions. There is a broad range of information that can eventually be acquired when recording an ecological interaction: from its simple presence (the interaction exists, it's been just recorded) to an estimate of its frequency, to obtaining data about its outcome or per-interaction effect (e.g., number of flowers pollinated in a visit by a pollinator to a plant). In addition, the types of interaction data can be quite diverse, reflecting the variety of sampling methods: interaction records from direct observation in the field; camera-traps; DNA-barcoding; bibliographic sources; surveys of image databases, etc. Interaction biodiversity inventories may require merging information coming from these distinct data sources. All these components need to be properly defined in order to build informative metadata and to document ecological interaction records. We are just starting to delineate the main components needed to catalog and inventory ecological interactions as a part of biodiversity inventories.

Exploring the nature and focus of feedback when using video playback in gynecology laparoscopy training

Background: Feedback about intraoperative performance remains a cornerstone of surgical training. Video playback offers one potential method for more effective feedback to surgical residents. More research is needed to better understand this method. This study explores the nature of instructional interactions and feedback in the operating room (OR) and when using video playback during post-operative review in obstetrics and gynecology (OBGYN) training. Method: This case study occurred between September 2016 and February 2017. Three OBGYN residents and five OBGYN supervising surgeons were involved in six laparoscopic cases. Intraoperative and video playback dialogues were recorded and analysed, the former deductively using codes identified from published literature, and the latter both deductively, using the same codes, and inductively, with codes that emerged from the data during analysis. Results: 1090 intraoperative interactions were identified within 376 minutes of dialogue. Most interactions were didactic, instructing the resident how to use an instrument to perform a task. Deductive analysis of postoperative video playback review identified 146 interactions within 155 minutes. While the most common interaction type remained didactic, a teaching component was included more often. It became apparent that deductive analysis using the intraoperative codes did not adequately capture the nature and focus of feedback during video playback. Hermeneutic phenomenological analysis identified more dialogic video playback sessions with more resident-initiated questions and reflection. Conclusions: This study demonstrates that the nature of feedback during video playback is fundamentally different from that in the OR, offering a greater potential for collaborative and improved learning.

Affective Engagement of Higher Education Students in an Online Course

The present research studies the factors that have impacted the affective engagement of university students in an educational online course. It examines how the type of interaction (learner-learner, learner-instructor, and learner-content) and the type of engagement (behavioural, cognitive and affective) have influenced the affective engagement of the students in the online course. Nineteen university students majoring in teaching mathematics, who were enrolled in the course Mathematics Teaching Methods, participated in the present research. Two data collection tools were used: semi-structured interviews and reflections. To analyse the texts resulting from the interviews and reflections, inductive and deductive qualitative content analysis was used. The research results indicated that university students have experienced more positive than negative affective engagement in the three communicational channels used in this course to facilitate online learning, which were: synchronous lectures, forums and assignments. The results also indicated that these three types of interaction have positively influenced students’ affective engagement in the three channels, with that influence being different from one channel to the other based on the interaction type taking place. We suggest that specific types of engagement need to be attended to for positive affect to occur. Doi: 10.28991/esj-2021-01296 Full Text: PDF

Accuracy and Precision of Social Relationship Indices

Combining interaction rates of different social behaviours into social relationship indices to represent the structure of dyadic relationships on one underlying dimension is common practice in animal sociality studies. However, the properties of these relationship indices are not well explored – mainly because, for real-world social systems, the ‘true’ value of relationships is unobservable. Here, we use simulation studies to estimate the accuracy and precision of three relationship indices: the Dyadic Composite Sociality Index, the Composite Relationship Index, and the Dynamic Dyadic Sociality Index. We simulated one year of social interactions for multiple groups of 25 individuals and 4 interaction types with different properties, and tested the impact of different focal follow regimes, data densities and sampling conditions on the representation of social relationships. Accuracy and precision of social relationship indices were strongly driven by sample size, similar to simple interaction rates. Under the assumption that there was a clear, one-dimensional relationship underlying interactions, and that different interaction types constituting an index were highly correlated, indices indeed increased accuracy over single interaction rates for small sample sizes. Including uninformative constituting behaviours (i.e., those not highly correlated with the underlying relationship dimension) reduced the accuracy of all indices. The precision of each index (i.e., whether multiple simulated focal follow regimes achieve the same dyadic values for the same data) was generally poor and was driven by the precision of the least precise constituting behaviour, making them less precise than some single interaction rates. Our results showed that social relationship indices do not remove the need to have sufficient data for each individual constituting interaction type. Index quality was defined by the least accurate and precise constituting interaction type. Indices might only be useful if all constituting interaction rates are highly correlated and if there are clear indications that one dimension is sufficient to represent social relationships in a group.

Hubungan Pemerintah Daerah dengan DPRD Kabupaten Kuantan Singingi dalam Penetapan APBD Tahun 2017

Determination of the budget and regional expenditure income (APBD) of Kuantan Singingi Regency has a polemic in the formulation process. The delay in the enactment of this regional budget regulation indicates that there is a bad relationship between the regional head and the Kuantan Singingi district parliament. To answer the problems that occur, an analysis is conducted to find the bright spots of the polemic. This research was conducted to see the relationship between the DPRD and local government in the process of formulating the APBD. This research uses a qualitative approach. Data collection techniques namely by studying literature and using previous research. This study uses Stone's interaction type theory, namely decisional type, anticipated reaction type, non-decisional making type, systemic type. The results showed that the relationship between the local government and the Regional Parliament of Kuantan Singingi in the formulation of the 2017 Regional Budget was included in the type of non-decisional making interaction. This type of interaction is a form of interaction that is influenced by the presence of a strong majority group in influencing the process of formulating the APBD, especially on the submission and agreement of the KUA-PPAS by providing public issues so that a bad image is formed.

Network motifs involving both competition and facilitation predict biodiversity in alpine plant communities

Biological diversity depends on multiple, cooccurring ecological interactions. However, most studies focus on one interaction type at a time, leaving community ecologists unsure of how positive and negative associations among species combine to influence biodiversity patterns. Using surveys of plant populations in alpine communities worldwide, we explore patterns of positive and negative associations among triads of species (modules) and their relationship to local biodiversity. Three modules, each incorporating both positive and negative associations, were overrepresented, thus acting as "network motifs." Furthermore, the overrepresentation of these network motifs is positively linked to species diversity globally. A theoretical model illustrates that these network motifs, based on competition between facilitated species or facilitation between inferior competitors, increase local persistence. Our findings suggest that the interplay of competition and facilitation is crucial for maintaining biodiversity.