Foray search: An effective systematic dispersal strategy in fragmented landscapes

In the absence of evidence to the contrary, population models generally assume that the dispersal trajectories of animals are random, but systematic dispersal could be more efficient at detecting new habitat and may therefore constitute a more realistic assumption. Here, we investigate, by means of simulations, the properties of a potentially widespread systematic dispersal strategy termed "foray search." Foray search was more efficient in detecting suitable habitat than was random dispersal in most landscapes and was less subject to energetic constraints. However, it also resulted in considerably shorter net dispersed distances and higher mortality per net dispersed distance than did random dispersal, and it would therefore be likely to lead to lower dispersal rates toward the margins of population networks. Consequently, the use of foray search by dispersers could crucially affect the extinction-colonization balance of metapopulations and the evolution of dispersal rates. We conclude that population models need to take the dispersal trajectories of individuals into account in order to make reliable predictions

Ecological and evolutionary processes at expanding range margins

Many animals are regarded as relatively sedentary and specialized in marginal parts of their geographical distributions. They are expected to be slow at colonizing new habitats. Despite this, the cool margins of many species' distributions have expanded rapidly in association with recent climate warming. We examined four insect species that have expanded their geographical ranges in Britain over the past 20 years. Here we report that two butterfly species have increased the variety of habitat types that they can colonize, and that two bush cricket species show increased fractions of longer-winged (dispersive) individuals in recently founded populations. Both ecological and evolutionary processes are probably responsible for these changes. Increased habitat breadth and dispersal tendencies have resulted in about 3- to 15-fold increases in expansion rates, allowing these insects to cross habitat disjunctions that would have represented major or complete barriers to dispersal before the expansions started. The emergence of dispersive phenotypes will increase the speed at which species invade new environments, and probably underlies the responses of many species to both past and future climate change

Non-random dispersal in the butterfly Maniola jurtina: implications for metapopulation models

The dispersal patterns of animals are important in metapopulation ecology because they affect the dynamics and survival of populations. Theoretical models assume random dispersal but little is known in practice about the dispersal behaviour of individual animals or the strategy by which dispersers locate distant habitat patches. In the present study, we released individual meadow brown butterflies (Maniola jurtina) in a non-habitat and investigated their ability to return to a suitable habitat. The results provided three reasons for supposing that meadow brown butterflies do not seek habitat by means of random flight. First, when released within the range of their normal dispersal distances, the butterflies orientated towards suitable habitat at a higher rate than expected at random. Second, when released at larger distances from their habitat, they used a non-random, systematic, search strategy in which they flew in loops around the release point and returned periodically to it. Third, butterflies returned to a familiar habitat patch rather than a non-familiar one when given a choice. If dispersers actively orientate towards or search systematically for distant habitat, this may be problematic for existing metapopulation models, including models of the evolution of dispersal rates in metapopulations

An Integrated Mechanistic Model of Mindfulness-Oriented Recovery Enhancement for Opioid-Exposed Mother–Infant Dyads

A growing body of neurobiological and psychological research sheds light on the mechanisms underlying the development and maintenance of opioid use disorder and its relation to parenting behavior. Perinatal opioid use is associated with risks for women and children, including increased risk of child maltreatment. Drawing from extant data, here we provide an integrated mechanistic model of perinatal opioid use, parenting behavior, infant attachment, and child well-being to inform the development and adaptation of behavioral interventions for opioid-exposed mother–infant dyads. The model posits that recurrent perinatal opioid use may lead to increased stress sensitivity and reward dysregulation for some mothers, resulting in decreased perceived salience of infant cues, disengaged parenting behavior, disrupted infant attachment, and decreased child well-being. We conclude with a discussion of Mindfulness-Oriented Recovery Enhancement as a means of addressing mechanisms undergirding perinatal opioid use, parenting, and attachment, presenting evidence on the efficacy and therapeutic mechanisms of mindfulness. As perinatal opioid use increases in the United States, empirically informed models can be used to guide treatment development research and address this growing concern

MitoSegNet: Easy-to-use Deep Learning Segmentation for Analyzing Mitochondrial Morphology

While the analysis of mitochondrial morphology has emerged as a key tool in the study of mitochondrial function, efficient quantification of mitochondrial microscopy images presents a challenging task and bottleneck for statistically robust conclusions. Here, we present Mitochondrial Segmentation Network (MitoSegNet), a pretrained deep learning segmentation model that enables researchers to easily exploit the power of deep learning for the quantification of mitochondrial morphology. We tested the performance of MitoSegNet against three feature-based segmentation algorithms and the machine-learning segmentation tool Ilastik. MitoSegNet outperformed all other methods in both pixelwise and morphological segmentation accuracy. We successfully applied MitoSegNet to unseen fluorescence microscopy images of mitoGFP expressing mitochondria in wild-type and catp-6ATP13A2 mutant C. elegans adults. Additionally, MitoSegNet was capable of accurately segmenting mitochondria in HeLa cells treated with fragmentation inducing reagents. We provide MitoSegNet in a toolbox for Windows and Linux operating systems that combines segmentation with morphological analysis

Copycat dynamics in leaderless animal group navigation

Background: Many animals are known to have improved navigational efficiency when moving together as a social group. One potential mechanism for social group navigation is known as the 'many wrongs principle', where information from many inaccurate compasses is pooled across the group. In order to understand how animal groups may use the many wrongs principle to navigate, it is important to consider how directional information is transferred and shared within the group. Methods: Here we use an individual-based model to explore the information-sharing and copying dynamics of a leaderless animal group navigating towards a target in a virtual environment. We assume that communication and information-sharing is indirect and arises through individuals partially copying the movement direction of their neighbours and weighting this information relative to their individual navigational knowledge. Results: We find that the best group navigation performance occurs when individuals directly copy the direction of movement of a subset of their neighbours while only giving a small (6%) weighting to their individual navigational knowledge. Surprisingly, such a strategy is shown to be highly efficient regardless of the level of individual navigational error. We find there is little relative improvement in navigational efficiency when individuals copy from more than 7 influential neighbours. Conclusions: Our findings suggest that we would expect navigating group-living animals to predominantly copy the movement of others rather than relying on their own navigational knowledge. We discuss our results in the context of individual and group navigation behaviour in animals

Communication and Cognition in Primate Group Movement

We here review the communicative and cognitive processes underpinning collective group movement in animals. Generally, we identify 2 major axes to explain the dynamics of decision making in animal or human groups or aggregations: One describes whether the behavior is largely determined by simple rules such as keeping a specific distance from the neighbor, or whether global information is also factored in. The second axis describes whether or not the individual constituents of the group have overlapping or diverging interests. We then review the available evidence for baboons, which have been particularly well studied, but we also draw from further studies on other nonhuman primate species. Baboons and other nonhuman primates may produce specific signals in the group movement context, such as the notifying behavior of male hamadryas baboons at the departure from the sleeping site, or clear barks that are given by chacma baboons that have lost contact with the group or specific individuals. Such signals can be understood as expressions of specific motivational states of the individuals, but there is no evidence that the subjects intend to alter the knowledge state of the recipients. There is also no evidence for shared intentionality. The cognitive demands that are associated with decision making in the context of group coordination vary with the amount of information and possibly conflicting sources of information that need to be integrated. Thus, selective pressures should favor the use of signals that maintain group cohesion, while recipients should be selected to be able to make the decision that is in their own best interest in light of all the available information

Swarm Intelligence in Animal Groups: When Can a Collective Out-Perform an Expert?

An important potential advantage of group-living that has been mostly neglected by life scientists is that individuals in animal groups may cope more effectively with unfamiliar situations. Social interaction can provide a solution to a cognitive problem that is not available to single individuals via two potential mechanisms: (i) individuals can aggregate information, thus augmenting their ‘collective cognition’, or (ii) interaction with conspecifics can allow individuals to follow specific ‘leaders’, those experts with information particularly relevant to the decision at hand. However, a-priori, theory-based expectations about which of these decision rules should be preferred are lacking. Using a set of simple models, we present theoretical conditions (involving group size, and diversity of individual information) under which groups should aggregate information, or follow an expert, when faced with a binary choice. We found that, in single-shot decisions, experts are almost always more accurate than the collective across a range of conditions. However, for repeated decisions – where individuals are able to consider the success of previous decision outcomes – the collective's aggregated information is almost always superior. The results improve our understanding of how social animals may process information and make decisions when accuracy is a key component of individual fitness, and provide a solid theoretical framework for future experimental tests where group size, diversity of individual information, and the repeatability of decisions can be measured and manipulated

Scalable Rules for Coherent Group Motion in a Gregarious Vertebrate

Individuals of gregarious species that initiate collective movement require mechanisms of cohesion in order to maintain advantages of group living. One fundamental question in the study of collective movement is what individual rules are employed when making movement decisions. Previous studies have revealed that group movements often depend on social interactions among individual members and specifically that collective decisions to move often follow a quorum-like response. However, these studies either did not quantify the response function at the individual scale (but rather tested hypotheses based on group-level behaviours), or they used a single group size and did not demonstrate which social stimuli influence the individual decision-making process. One challenge in the study of collective movement has been to discriminate between a common response to an external stimulus and the synchronization of behaviours resulting from social interactions. Here we discriminate between these two mechanisms by triggering the departure of one trained Merino sheep (Ovis aries) from groups containing one, three, five and seven naïve individuals. Each individual was thus exposed to various combinations of already-departed and non-departed individuals, depending on its rank of departure. To investigate which individual mechanisms are involved in maintaining group cohesion under conditions of leadership, we quantified the temporal dynamic of response at the individual scale. We found that individuals' decisions to move do not follow a quorum response but rather follow a rule based on a double mimetic effect: attraction to already-departed individuals and attraction to non-departed individuals. This rule is shown to be in agreement with an adaptive strategy that is inherently scalable as a function of group size

Small DNA Pieces in C. elegans Are Intermediates of DNA Fragmentation during Apoptosis

While studying small noncoding RNA in C. elegans, we discovered that protocols used for isolation of RNA are contaminated with small DNA pieces. After electrophoresis on a denaturing gel, the DNA fragments appear as a ladder of bands, ∼10 nucleotides apart, mimicking the pattern of nuclease digestion of DNA wrapped around a nucleosome. Here we show that the small DNA pieces are products of the DNA fragmentation that occurs during apoptosis, and correspondingly, are absent in mutant strains incapable of apoptosis. In contrast, the small DNA pieces are present in strains defective for the engulfment process of apoptosis, suggesting they are produced in the dying cell prior to engulfment. While the small DNA pieces are also present in a number of strains with mutations in predicted nucleases, they are undetectable in strains containing mutations in nuc-1, which encodes a DNase II endonuclease. We find that the small DNA pieces can be labeled with terminal deoxynucleotidyltransferase only after phosphatase treatment, as expected if they are products of DNase II cleavage, which generates a 3′ phosphate. Our studies reveal a previously unknown intermediate in the process of apoptotic DNA fragmentation and thus bring us closer to defining this important pathway