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1,140 results for “Colony”
Drivers of alloparental provisioning of fledglings in a colonially-breeding bird
Offspring provisioning represents a major reproductive cost. However, evidence suggests that parents sometimes feed unrelated offspring. Several hypotheses could explain this puzzling phenomenon. Adults could feed unrelated offspring that are (1) of close social associates to facilitate these juveniles' integration into their social network (resulting in social inheritance), (2) potential extra-pair offspring, (3) at a similar developmental stage as their own, (4) coercing feeding by begging, or (5) less-developed and who's enhanced survival would benefit the adult or its own offspring (the group augmentation hypothesis). Colonial breeders are ideal for investigating the relative importance of these hypotheses because offspring are often kept in crèches where adults can exhibit allofeeding. Using automated monitoring of replicated captive zebra finch (Taeniopygia guttata) colonies, we found that while parents selectively fed their own offspring, they also consistently fed unrelated offspring (32.48% of feeding events). Social relationships among adults prior to breeding did not predict allofeeding, nor was provisioning directed towards unrelated offspring directed to potential genetic offspring. Instead, adults preferentially fed less-developed non-offspring, despite these not begging more frequently than larger ones did. Our study suggests that allofeeding is consistent with group augmentation, which could be beneficial through colony maintenance or increased offspring survival.
Bumblebee colony density on farmland is influenced by late-summer nectar supply and garden cover
<p>1. Floral resources are important in limiting pollinator populations, but they are often highly variable across time and space and the effect of this variation on pollinator population dynamics is not well understood. The phenology (timing) of floral resources is thought to be important in structuring pollinator populations, but few studies have directly investigated this. 2. Our study quantifies the landscape composition, seasonal nectar and pollen supply, and <i>Bombus terrestris</i> colony density of 12 farms in southwest UK to investigate how landscape composition influences the phenology of floral resources and how both these factors affect colony density. We use this information in a spatially explicit predictive model to estimate the effect of different farmland management scenarios on seasonal resource supplies and colony density. 3. We find that farmland nectar supply during September is a strong predictor of <i>B. terrestris</i> colony density in the following year, explaining over half of all the variation in colony density; no other period of resource availability showed a significant association. Semi-natural habitat cover was not a good proxy for nectar or pollen supply and showed no significant association with colony density. However, the proportional cover of gardens in the landscape was significantly associated with colony density. 4. The predictive model results suggest that increasing the area of semi-natural flowering habitat has limited effect on bumblebee populations. However, improving the quality of these habitats through Environmental Stewardship and other management options is predicted to reduce the late-summer resource bottleneck and increase colony density. 5. Synthesis and Applications: Our results demonstrate the importance of considering the phenology of resources, rather than just total resource availability, when designing measures to support pollinators. Late-summer appears to be a resource bottleneck for bumblebees in UK farmland, and consequently management strategies which increase late-summer nectar availability may be the most effective. These include mowing regimes to delay flowering of field margins until September, planting late-flowering cover crops such as red clover, and supporting late-flowering wild plant species such as <i>Hedera helix</i>. Our results also suggest that rural gardens may play an important role in supporting farmland bumblebee populations.</p>
Data from: Context-dependent expression of the foraging gene in field colonies of ants: the interacting roles of age, environment and task
Task allocation among social insect workers is an ideal framework for studying the molecular mechanisms underlying behavioural plasticity because workers of similar genotype adopt different behavioural phenotypes. Elegant laboratory studies have pioneered this effort, but field studies involving the genetic regulation of task allocation are rare. Here, we investigate the expression of the foraging gene in harvester ant workers from five age- and task-related groups in a natural population, and we experimentally test how exposure to light affects foraging expression in brood workers and foragers. Results from our field study show that the regulation of the foraging gene in harvester ants occurs at two time scales: levels of foraging mRNA are associated with ontogenetic changes over weeks in worker age, location and task, and there are significant daily oscillations in foraging expression in foragers. The temporal dissection of foraging expression reveals that gene expression changes in foragers occur across a scale of hours and the level of expression is predicted by activity rhythms: foragers have high levels of foraging mRNA during daylight hours when they are most active outside the nests. In the experimental study, we find complex interactions in foraging expression between task behaviour and light exposure. Oscillations occur in foragers following experimental exposure to 13 L : 11 D (LD) conditions, but not in brood workers under similar conditions. No significant differences were seen in foraging expression over time in either task in 24 h dark (DD) conditions. Interestingly, the expression of foraging in both undisturbed field and experimentally treated foragers is also significantly correlated with the expression of the circadian clock gene, cycle. Our results provide evidence that the regulation of this gene is context-dependent and associated with both ontogenetic and daily behavioural plasticity in field colonies of harvester ants. Our results underscore the importance of assaying temporal patterns in behavioural gene expression and suggest that gene regulation is an integral mechanism associated with behavioural plasticity in harvester ants.
Data from: Non-clonal coloniality: genetically chimeric colonies through fusion of sexually produced polyps in the hydrozoan Ectopleura larynx
Hydrozoans typically develop colonies through asexual budding of polyps. Although colonies of Ectopleura are similar to other hydrozoans in that they consist of multiple polyps physically connected through continuous epithelia and shared gastrovascular cavity, Ectopleura larynx does not asexually bud polyps indeterminately. Instead, after an initial phase of limited budding in a young colony, E. larynx achieves its large colony size through the aggregation and fusion of sexually (non-clonally) produced polyps. The apparent chimerism within a physiologically integrated colony presents a potential source of conflict between distinct genetic lineages, which may vary in their ability to access the germline. In order to determine the extent to which the potential for genetic conflict exists, we characterized the types of genetic relationships between polyps within colonies, using a RAD-Seq approach. Our results indicate that E. larynx colonies are indeed comprised of polyps that are clones and sexually reproduced siblings and offspring, consistent with their life history. In addition, we found that colonies also contain polyps that are genetically unrelated, and that estimates of genome-wide relatedness suggests a potential for conflict within a colony. Taken together, our data suggests that there are distinct categories of relationships in colonies of E. larynx, likely achieved though a range of processes including budding, regeneration and fusion of progeny and unrelated polyps, with the possibility for a genetic conflict resolution mechanism. Together these processes contribute to the re-evolution of the ecologically important trait of coloniality in E. larynx.
Data from: Colony personality and plant health in the Azteca-Cecropia mutualism
For interspecific mutualisms, the behavior of one partner can influence the fitness of the other, especially in the case of symbiotic mutualisms where partners live in close physical association for much of their lives. Behavioral effects on fitness may be particularly important if either species in these long-term relationships displays personality. We conducted a field study on collective personality in Azteca constructor colonies that live in Cecropia trees, one of the most successful and prominent mutualisms of the neotropics. These pioneer plants provide hollow internodes for nesting and nutrient-rich food bodies; in return, the ants provide protection from herbivores and encroaching vines. We tested the consistency and correlation of five colony-level behavioral traits, censused colonies, and measured the amount of leaf damage for each plant. Four of five traits were both consistent within colonies and correlated among colonies. This reveals a behavioral syndrome along a docile-aggressive axis, with higher-scoring colonies showing greater activity, aggression, and responsiveness. Scores varied substantially between colonies and were independent of colony size and age. Host plants of more active, aggressive colonies had less leaf damage, suggesting a link between a colony's personality and effective defense of its host, though the directionality of this link remains uncertain. Our field study shows that colony personality is an ecologically relevant phenomenon and sheds light on the importance of behavioral differences within mutualism dynamics.
Wolbachia-infected ant colonies have increased reproductive investment and an accelerated life cycle
<p><b><em>Wolbachia </em>is a widespread group of maternally-transmitted endosymbiotic bacteria that often manipulates the reproductive strategy and life history of its hosts to favor its own transmission. <em>Wolbachia </em></b><b>mediated phenotypic effects are well characterized in solitary hosts, although evidence of similar effects are rare in eusocial insects, such as ants. The invasive pharaoh ant, <em>Monomorium pharaonis</em>, shows natural variation in </b><b><em>Wolbachia </em></b><b>infection between colonies and can be readily bred under laboratory conditions. We previously showed that </b><b><em>Wolbachia</em></b><b>-infected pharaoh ant colonies had a queen-biased sex ratio, which is expected to favor the spread of maternally-transmitted </b><b><em>Wolbachia</em></b><b>. Here, we further characterize the effects of </b><b><em>Wolbachia </em></b><b>on the short- and longer-term reproductive and life history traits of pharaoh ant colonies. First we characterized reproductive differences between naturally infected and uninfected colonies at three discrete time points and found that infected colonies had higher reproductive investment (i.e. infected colonies produce more new queens), in particular when colony queens were three months old. Next, we compared the long-term growth and reproduction dynamics of infected and uninfected colonies across their whole life cycle. Infected colonies had increased colony-level growth and early colony reproduction, resulting in a shorter colony life cycle, when compared to uninfected colonies. </b></p>
Data from: Ant community and habitat limit colony establishment by the fire ant, Solenopis invicta
Hypotheses of community assembly include limitation through habitat physical attributes, as well as competition among species. Such hypotheses must be resolved through experimental tests. Previous experiments have shown that: (i) fire ants of the monogyne social form occur mostly in highly disturbed habitat where they do not compete with mature colonies of co-occurring ants; (ii) in native pine forests of northern Florida, habitat disturbance favours fire ants while simultaneously reducing native ants; (iii) fire ants thrive in these disturbances but do not persist as these become less disturbed over time; and finally, (iv) newly mated, dispersing/colony-founding fire ant queens settle preferentially in such disturbed sites. We now show that by choosing disturbed sites, newly mated, monogyne fire ant queens greatly increase their chances of successful colony establishment. Experimental plots were created in the native ground cover of a north Florida pine forest with all combinations of tilling, shading or reduction of the native ant community. Newly mated fire ant queens, incipient colonies and small colonies were planted in these plots. Only five of 980 (0·5%) newly mated queen nests survived after 120 days, and only five of 400 incipient colonies (1·3%) survived after 30 days. All survivors were in plots with tilling and/or native ant reduction. Extrapolation indicated that 0·04% of newly mated queens and 0·1% of incipient colonies were likely to have survived at 1 year. In contrast, planting small colonies resulted in much higher rates of survival – in plots with native ant reduction, fire ants increased on baits throughout the year but decreased in unreduced control plots. Fifteen months after planting 108 colonies, 21 mounds (19%) were found in the ant-reduced plots, but <2% of 108 colonies survived in the control plots. Taken together, these results show that by landing in disturbed habitat with its reduced native ant population, newly mated fire ants queens increase their chances of successful colony establishment. In contrast to much of the previous literature, our results suggest that ant community assembly proceeds primarily by queen habitat choice and secondarily by filtering and competition.
Data from: Day/night upper thermal limits differ within Ectatomma ruidum ant colonies
In the tropics, daily temperature fluctuations can pose physiological challenges for ectothermic organisms, and upper thermal limits may affect foraging activity over the course of the day. Variation in upper thermal limits can occur among and within species, and for social insects such as ants, within colonies. Within colonies, upper thermal limits may differ among individuals or change for an individual throughout the day. Daytime foragers of the Neotropical ant Ectatomma ruidum have higher critical thermal maxima (CTmax) than nocturnal foragers, but whether these differences occur among or within colonies was not previously known. We investigated the potential mechanisms accounting for day/night variation in CTmax of E. ruidum foragers by testing whether CTmax varied among or within colonies or due to individuals within colonies acclimating to changes in temperature over a short time scale (3 h). We found within- but not among-colony differences in CTmax on a diel cycle, and we found no evidence for among- or within-colony partitioning of foraging times by individual workers. Individuals did not acclimate to experimental manipulations of temperature, although additional experiments with more ecologically relevant temperature manipulations are needed to rule out this mechanism. In summary, we have shown that day/night differences in upper thermal limits can occur within ant colonies, but further investigation is needed to elucidate the mechanisms driving this variation.
Data from: Flowering plant composition shapes pathogen infection intensity and reproduction in bumble bee colonies
<p><span>Pathogens pose significant threats to pollinator health and food security. Pollinators can transmit diseases during foraging, but the consequences of plant species composition for infection is unknown. In agroecosystems, flowering strips or hedgerows are often used to augment pollinator habitat. We used canola as a focal crop in tents, and manipulated flowering strip composition using plant species we had previously shown to result in higher or lower bee infection in short-term trials. We also manipulated initial colony infection to assess impacts on foraging behavior. Flowering strips using high-infection plant species nearly doubled bumble bee colony infection intensity compared to low-infection plant species, with intermediate infection in canola-only tents. Both infection treatment and flowering strips reduced visits to canola, but we saw no evidence that infection treatment shifted foraging preferences. Although high-infection flowering strips increased colony infection intensity, colony reproduction was improved with any flowering strips compared to canola alone. Effects of flowering strips on colony reproduction were explained by nectar availability, but effects of flowering strips on infection intensity were not. Thus, flowering strips benefited colony reproduction by adding floral resources, but certain plant species also come with a risk of increased pathogen infection intensity.</span></p>
P colonies and P swarms for controlling robot swarms. Experimental setups and demonstration videos
<p>These eleven videos present different experimental scenarios used to test the flexibility and functioning of the LULU P colony/P swarm simulator and of the associated application Lulu_Kilobot for controlling robot swarms. Both applications will be published on Github under an open-source license. The input P colony (input) file, swarm configuration (config) file and V-REP scene (.ttt) are available for each video in the associated .zip archive.</p> <p>The LULU simulator was included as a Python module in Lulu_Kilobot in order to test robot controllers based on P colonies, XP colonies, and P swarms for swarms of up to 10 Kilobot robots.</p> <p>In the following sections, we present a small description for each of the eleven attached videos.</p> <p>-----------------------------------------------------------------------------------------------<br /> 1_clone_10_circle</p> <p>This video demonstrates the use of the robot cloning function of the vrep_bridge script in order to create 9 distinct copies of the source robot and distribute them on a circle around the source robot. The copies are so positioned by a distribution function that can be adapted to other forms. This cloning function allows one to generate large swarms of robots with ease.</p> <p>-----------------------------------------------------------------------------------------------<br /> 2_one_pcolony_for_three_kilobots</p> <p>In this video, we simulate a simple P minus colony using Lulu_Kilobot, on three different robots. At each subtraction, the robots move one step forward. At the beginning of the clip one can see the Robot - P colony association table, where each robot has a distinct copy of the original P colony.</p> <p>-----------------------------------------------------------------------------------------------<br /> 3_pswarm_5_robots_3_colonies</p> <p>This video demonstrates the flexibility offered by the config file of Lulu_Kilobot. From the config file we explicitly specify that the first two robots should use the go straight P colony. For the other colonies, we specify the number of robots that should be assigned, go left = 1 and go right = 2.</p> <p>From the Robot - P colony association table, one can see that the first robot that is assigned a P colony uses the original P colony while the others use an independent copy of the P colony.</p> <p>-----------------------------------------------------------------------------------------------<br /> 4_pswarm_2_robots_avoid_collision</p> <p>In this experiment, we test the msg_distance agent from the input module, by continuously checking the distance from another robot.</p> <p>If the distance is short, then we stop the movement and otherwise continue to subtract f objects from the environment and move forward.</p> <p>Each of the two robots has a different P colony that was designed to check the distance from the other robot (robot_0 checks the distance from robot_1).</p> <p>-----------------------------------------------------------------------------------------------<br /> 5_pswarm_2_robots_xp_colonies_15_steps</p> <p>In this video we employ the exteroceptive communication rules (denoted by <=>) in order to synchronize the movement of two robots. The first robot moves forward 15 steps and after it stops, it signals the second robot to start moving. At this signal, the second robot starts to turn left 15 steps.</p> <p>This shows the utility of exteroceptive rules that allow XP colonies (P colonies with exteroceptive rules) to communicate using the global P swarm environment.</p> <p>-----------------------------------------------------------------------------------------------<br /> 6_1_pswarm_10_robots_disperse_steps_infinite_loop</p> <p>In this video we run a more complex algorithm that involves the use of the following modules: msg_distance, led_rgb, and motion.</p> <p>This video demonstrates dispersion, which is a typical self-deploying scenario in swarm robotics. The robots should position themselves away from one another, so that each robot is at least at a minimum distance from each of its neighbours.</p> <p>All decisions are taken by the command module, on the basis of the received input data from msg_distance. A new direction of motion (and color) is randomly chosen if there are other robots closer than a pre-set threshold distance.</p> <p>-----------------------------------------------------------------------------------------------<br /> 6_2_pswarm_10_robots_optimized_disperse_infinite_loop</p> <p>This video is an optimized version of 6.1 (10 robots disperse).</p> <p>The optimization consists in only exchanging data with V-REP when a new input request is detected in the input agents or likewise a new command object is detected in the output agents.</p> <p>This results in a step-less movement of the robots and reduces the time needed for a new decision to be applied resulting in a faster overall simulation time.</p> <p>-----------------------------------------------------------------------------------------------<br /> 7_pswarm_10_robots_optimized_disperse_infinite_loop_with_intruder</p> <p>In this video we use the previously presented optimized dispersion algorithm (6.2) and introduce an intruder robot into the scene in order to evaluate the influence that this intruder has over the behaviour of the swarm.</p> <p>One can see that robots that have stopped their movement, restart dispersing when the intruder robot is brought close enough. This can cause a chain reaction and ultimately cause the swarm to reposition.</p> <p>-----------------------------------------------------------------------------------------------<br /> 8_1_pswarm_10_robots_secure_disperse_fast</p> <p>In this video we test the proposed security protocol (based on entity authentification and P colony based id check) using the non-optimized dispersion algorithm.</p> <p>In this film we see that the robots ignore the intruder robot even though it is placed in the middle of the swarm. On the other hand, if we bring a swarm member robot close to another swarm member robot, these two will start to disperse normally.</p> <p>-----------------------------------------------------------------------------------------------<br /> 8_2_pswarm_10_robots_secure_disperse_infinite_loop_2</p> <p>In this video we present the optimized (see 6.2 for details) version of the secured dispersion algorithm.</p> <p>As was the case of the secured un-optimized version (8.1), in this secured version we test the influence of the intruder on the behaviour of the swarm by moving the intruder close to the center of the swarm and also moving the intruder close to the swarm after the dispersion is finished. We also note that if two member robots approach, the algorithm continues to work normally.</p> <p>-----------------------------------------------------------------------------------------------<br /> 9_pswarm_10_robots_secure_d_min_disperse_infinite_loop</p> <p>In this clip we show the effects of transparent input data processing.</p> <p>The command agent always requests the smallest distance available from the neighbour list, by using the d_min command.</p> <p>When the intruder robot is the nearest robot (the smallest value in the list) d_min will always return the intruder robot which cannot be processed because it is unknown to the swarm members. For this reason, a member robot that is in this situation will be blocked by the intruder robot.</p>
Lulu - a software simulator for P colonies. Use case scenarios and demonstration videos
<p>The videos show three different examples of using the Lulu P colony simulator.</p> <p>The Lulu P colony simulator is available under an open-source MIT license at https://github.com/andrei91ro/lulu_pcol_sim. All of the secondary applications, including Lulu_Kilobot are available (also under open-source licenses) at https://github.com/andrei91ro.</p> <p>The first two videos present the simulator running addition (+1) and subtraction (-1). In these two examples, the simulator is ran in a step by step mode in order to clearly visualize the results of running each simulation step. For this reason the total simulation time reported at the end of the simulation is in the order of minutes.</p> <p>The average (of five runs) simulation time for a normal (non-interactive) simulation is 0.0021050 seconds for the addition and 0.0047492 seconds for the subtraction examples.</p> <p>The third example (lulu_kilobot_30_steps) presents the simulator running a more complex P colony that controls a Kilobot robot simulated in V-REP. This P colony is based on the subtraction P colony in the sense that each move the robot makes is marked by the removal of an f object from the environment.</p> <p>The input file used in the addition example (lulu_sim_ag_increment):</p> <p>pi = {<br /> A = {l_p};<br /> e = e;<br /> f = f;<br /> n = 2;<br /> env = {f, f, f, l_p};<br /> B = {AG_1};<br /> AG_1 = ({e, e}; < e->f, e<->l_p >, < l_p->e, f<->e >);<br /> }</p> <p>The input file used in the subtraction example (lulu_sim_ag_decrement):</p> <p>pi = {<br /> A = {l_m, l_p, l_z};<br /> e = e;<br /> f = f;<br /> n = 2;<br /> env = {f, f, f, l_m};<br /> B = {AG_1};<br /> AG_1 = ({e, e};<br /> < e->e, e<->l_m >,<br /> < l_m->l_p, e<->f/e<->e >,<br /> < f->e, l_p<->e >,<br /> < l_p->l_z, e<->e >,<br /> < e->e, l_z<->e > );<br /> }</p> <p>The input file used in the Kilobot example (lulu_kilobot_30_steps):</p> <p>pi = {<br /> A = {l_m, m_0, m_S, m_L, m_R, c_R, c_G, c_B};<br /> e = e;<br /> f = f;<br /> n = 2;<br /> env = {f, f, f, f, f, f, f, f, f, f, f, f, f, f, f, f, f, f, f, f, f, f, f, f, f, f, f, f, f, f, l_m};<br /> B = {AG_command, AG_motion};<br /> AG_command = ({e, e};<br /> < e->e, e<->l_m >,<br /> < l_m->m_S, e<->f/e<->e >,<br /> < f->e, m_S<->e >,<br /> < m_S->m_0, e<->e >,<br /> < e->e, m_0<->e > );</p> <p> AG_motion = ({e, e};<br /> < e->l_m, e<->m_S >,<br /> < m_S->e, l_m<->e/e->e ><br /> < e->e, e<->m_0 >,<br /> < m_0->e, e<->m_0/e->e >);<br /> }</p> <p> </p>
Data from: Stress-induced loss of social resilience in honeybee colonies and its implications on fitness
<p>Stressors may lead to a shift in the timing of life-history events of species causing a mismatch with optimal environmental conditions, potentially reducing fitness. In honeybees, the timing of brood rearing and nest emergence in late winter/early spring is critical, as colonies need to grow fast after winter to prepare for reproduction. However, the effects of stress on these life-history events in late winter/early spring and the possible consequences are not well understood. Therefore, we tested whether (1) honeybee colonies shift timing of brood rearing and nest emergence as a response to stressors, and (2) if there is a consequent loss of social resilience, reflected in colony fitness (survival, growth and reproduction). We monitored stressed (high load of the parasitic mite <em>Varroa destructor</em> or nutrition-restricted) colonies and presumably non-stressed colonies from the beginning of 2020 till the spring of 2021. We found that honeybee colonies do not shift the timing of brood rearing and nest emergence in spring as a coping mechanism to stressors. However, we show that there is a loss of social resilience in stressed colonies, leading to reduced growth and reproduction. Our study contributes to a better understanding of the effects of stressors on social resilience in eusocial organisms.</p>
Genomics polymorphisms of Staphylococcus aureus strain NCTC 8325 in the lab stock maintained at TUM (WT), after 30 passes in BHI media (D) and after 30 passes detecting 4 -fold MIC increase to isocyanide -code I16- 3 biological replicates (A,B,C), and 3 independent colonies sequenced per replicate at the end of the experiment.
<p>Genomics polymorphisms of Staphylococcus aureus strain NCTC 8325 in the lab stock maintained at TUM (WT), after 30 passes in BHI media (D) and after 30 passes detecting 4 -fold MIC increase to isocyanide -code I16- 3 biological replicates (A,B,C), and 3 independent colonies sequenced per replicate at the end of the experiment. Determined from Illumina shotgun genomic sequencing datasets, mapping and analyses vs the reference genome of the strain https://www.ncbi.nlm.nih.gov/nuccore/NC_007795.1/</p>
Fig. 1. Map showing a in Graveyards of Giant Pandas at the Bottom of the Sea? A Strange-Looking New Species of Colonial Ascidians in the Genus Clavelina (Tunicata: Ascidiacea)
Fig. 1. Map showing a sampling locality, Tonbara, off Kumejima Island, Japan.
Data from: Range-wide genetic analysis of an endangered bumble bee (Bombus affinis) reveals population structure, isolation by distance, and low colony abundance
<p>Declines in bumblebee species ranges and abundances are documented across multiple continents and have prompted the need for research to aid species recovery and conservation. The rusty patched bumblebee (<em>Bombus affinis</em>) is the first federally-listed bumblebee species in North America. We conducted a range-wide population genetics study of <em>B. affinis</em> from across all extant conservation units to inform conservation efforts. To understand the species' vulnerability and help establish recovery targets, we examined population structure, patterns of genetic diversity, and population differentiation. Additionally, we conducted site-level analysis of colony abundance to inform prioritizing areas for conservation, translocation, and other recovery actions. We find substantial evidence of population structuring along an east-to-west gradient. Putative populations show evidence of isolation by distance, high inbreeding coefficients, and a range wide male diploidy rate of ~15%. Our results suggest the Appalachians represents a genetically distinct cluster with high levels of private alleles and substantial differentiation from the rest of the extant range. Site-level analyses suggest low colony abundance estimates for <em>B. affinis</em> compared to similar datasets of stable, co-occurring species. These results lend genetic support to trends from observational studies suggesting B. affinis has undergone a recent decline and exhibits substantial spatial structure. The low colony abundances observed here suggest caution in overinterpreting the stability of populations even where <em>B. affinis</em> is reliably detected interannually. These results help delineate informed management units, provide context for the potential risks of translocation programs, and can help set clear recovery targets for this and other threatened bumblebee species.</p>
Carotenoid skin ornaments as flexible indicators of male foraging behavior in a marine predator: Variation among Mexican colonies of Brown Booby (Sula leucogaster)
<p>Carotenoid-dependent ornaments can reflect animals' diet and foraging behaviors. However, this association should be spatially flexible and variable among populations to account for geographic variation in optimal foraging behaviors. We tested this hypothesis using populations of a marine predator (the brown booby, <em>Sula leucogaster</em>) that forage across a gradient in ocean depth in and near the Gulf of California. Specifically, we quantified green chroma for two skin traits (foot and gular color) and their relationship to foraging location and diet of males, as measured via GPS tracking and stable carbon isotope analysis of blood plasma. Our three focal colonies varied in which foraging attributes were linked to carotenoid-rich ornaments. For gular skin, our data showed a shift from a benthic prey-green skin association in the shallow waters in the north to a pelagic prey-green skin association in the deepest waters to the south. Mean foraging trip duration and distance of the foraging site from the coast also predicted skin coloration in some colonies. Finally, brown booby colonies varied in which trait (foot vs. gular skin color) was associated with foraging metrics. Overall, our results indicate that male ornaments reflect the quality of diet and foraging – information that may help females select mates who are adapted to local foraging conditions and therefore, are likely to provide better parental care. More broadly, our results stress that diet-dependent ornaments are intimately linked to animals' environments and that we cannot assume ornaments or ornament signal content are ubiquitous within species, even when ornaments appear similar among populations. </p>
Figure 2 in Species diversity and composition of Oribatida (Acari: Sarcoptiformes) in former breeding colonies of the great cormorant (Phalacrocorax carbo) in Poland
Figure 2. Number of species from individual ecological groups in each studied site.
Figure 1 in Species diversity and composition of Oribatida (Acari: Sarcoptiformes) in former breeding colonies of the great cormorant (Phalacrocorax carbo) in Poland
Figure 1. The abundance of oribatid mites from individual ecological groups in each studied site.
Behavioral flexibility in solitary foraging ants: how experience, colony size and food distribution shape individual and collective performance
<p>To deal with the unpredictability of available food resources, animals must adjust their behavior to optimize foraging efficiency. Various mechanisms can influence an individual’s food acquisition behaviour, and thus our knowledge of their combined impact on foraging efficiency remains limited. In this study, we conducted laboratory experiments with seven colonies of the solitary foraging ant Dinoponera quadriceps. Foragers were individually observed in semi-controlled experiments where food was offered in aggregated or dispersed distributions. During the experiments, individual participation was voluntary (i.e. ants were free to enter or not the experimental arena), giving us an opportunity to assess internal processes such as motivation. Besides, behavioral traits such as foraging activity, exploration of food patches, and performance were recorded across repeated trials. We found that solitary foragers of D. quadriceps were highly efficient (retrieving food in 77.38% of the trips), especially when exploiting aggregated and abundant food resources. However, individual foraging success declined when more conspecific foragers were present and with longer foraging experience. Foragers increased their exploration levels in environments with larger numbers of dispersed prey items. Individual foraging activity was higher with more experience and in smaller colonies with fewer foragers. Furthermore, foragers and colonies exhibited low but consistent differences in levels of activity, exploration, and success rates. These findings provide a comprehensive view of how different factors combine to give rise to complex behaviors such as foraging. Additionally, they emphasize the importance of individual traits for effective task performance within social groups, an understudied topic.</p>
Supplementary material S24: Time course of the loudest Varroa jolting pulse compared to that of a honeybee colony and single bee individual.
<p>Time course of the loudest <em>Varroa </em>jolt on brood-comb with the signal from the full colony and a single bee. The signal seen here in each panel is the integral of the magnitude of acceleration with respect to time. The background vibration that is inherent to the room was calculated and subtracted from this data. The loudest jolt (red) is here compared to the signal of a single bee (black) and the vibrations of the full colony at low and high signal (black). High signal is captured when the frame containing the accelerometer is empty of brood. Low signal is captured when the frame is fully loaded with brood and/or honey. The whooping signal (panel a) was captured during a period of high signal.</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.