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Structural aluminum alloys are often less-than ideal materials for studying sub-grain strain gradients via EBSD, at typical resolution settings. Sharply defined slip bands are not generally observed due to cross-slip, and secondphase particles formed during solidification of work-hardened alloys provide obstacles that disrupt potential structure development, leading to what can seem like random distributions of geometrically necessary dislocations (GNDs). This study considers the roles of length-scale and second-phase particles in sub-grain distributions of AA6016-T4 following deformation. Second-phase particles are shown to play a stronger role than grain boundaries (GBs) in local GND accumulations. The net Burgers vector is used to show the transition from crystallographic-level slip to macro-scale slip as length scale increases, with a corresponding transition in the GND vs. step size graph. A strain gradient crystal plasticity model is applied to assess predictability of the observations. Real 3D structures were extracted, via serial sectioning, following application of different strain paths. Predicted GND and total dislocation evolution closely follows observed values. The model is then used to study the relative contributions of GBs and second-phase particles to GND localization, leading to the conclusion that second-phase particles must be included in the model to reflect observed behavior. 

Abstract Most studies assessing rates of phenotypic change focus on population mean trait values, whereas a largely overlooked additional component is changes in population trait variation. Theoretically, eco‐evolutionary dynamics mediated by such changes in trait variation could be as important as those mediated by changes in trait means. To date, however, no study has comprehensively summarised how phenotypic variation is changing in contemporary populations. Here, we explore four questions using a large database: How do changes in trait variances compare to changes in trait means? Do different human disturbances have different effects on trait variance? Do different trait types have different effects on changes in trait variance? Do studies that established a genetic basis for trait change show different patterns from those that did not? We find that changes in variation are typically small; yet we also see some very large changes associated with particular disturbances or trait types. We close by interpreting and discussing the implications of our findings in the context of eco‐evolutionary studies. 

Abstract Eco‐evolutionary experiments are typically conducted in semi‐unnatural controlled settings, such as mesocosms; yet inferences about how evolution and ecology interact in the real world would surely benefit from experiments in natural uncontrolled settings. Opportunities for such experiments are rare but do arise in the context of restoration ecology—where different “types” of a given species can be introduced into different “replicate” locations. Designing such experiments requires wrestling with consequential questions. (Q1) Which specific “types” of a focal species should be introduced to the restoration location? (Q2) How many sources of each type should be used—and should they be mixed together? (Q3) Whichspecificsource populations should be used? (Q4) Which type(s) or population(s) should be introduced into which restoration sites? We recently grappled with these questions when designing an eco‐evolutionary experiment with threespine stickleback (Gasterosteus aculeatus) introduced into nine small lakes and ponds on the Kenai Peninsula in Alaska that required restoration. After considering the options at length, we decided to use benthic versus limnetic ecotypes (Q1) to create a mixed group of colonists from four source populations of each ecotype (Q2), where ecotypes were identified based on trophic morphology (Q3), and were then introduced into nine restoration lakes scaled by lake size (Q4). We hope that outlining the alternatives and resulting choices will make the rationales clear for future studies leveraging our experiment, while also proving useful for investigators considering similar experiments in the future. 

Abstract Wild populations must continuously respond to environmental changes or they risk extinction. Those responses can be measured as phenotypic rates of change, which can allow us to predict contemporary adaptive responses, some of which are evolutionary. About two decades ago, a database of phenotypic rates of change in wild populations was compiled. Since then, researchers have used (and expanded) this database to examine phenotypic responses to specific types of human disturbance. Here, we update the database by adding 5675 new estimates of phenotypic change. Using this newer version of the data base, now containing 7338 estimates of phenotypic change, we revisit the conclusions of four published articles. We then synthesize the expanded database to compare rates of change across different types of human disturbance. Analyses of this expanded database suggest that: (i) a small absolute difference in rates of change exists between human disturbed and natural populations, (ii) harvesting by humans results in higher rates of change than other types of disturbance, (iii) introduced populations have increased rates of change, and (iv) body size does not increase through time. Thus, findings from earlier analyses have largely held‐up in analyses of our new database that encompass a much larger breadth of species, traits, and human disturbances. Lastly, we use new analyses to explore how various types of human disturbances affect rates of phenotypic change, and we call for this database to serve as a steppingstone for further analyses to understand patterns of contemporary phenotypic change.