There is increasing evidence that intense fishing pressure is not only depleting fish stocks but also causing evolutionary changes to fish populations. In particular, body size and fecundity in wild fish populations may be altered in response to the high and often size‐selective mortality exerted by fisheries. While these effects can have serious consequences for the viability of fish populations, there are also a range of traits not directly related to body size which could also affect susceptibility to capture by fishing gears—and therefore fisheries‐induced evolution (FIE)—but which have to date been ignored. For example, overlooked within the context of FIE is the likelihood that variation in physiological traits could make some individuals within species more vulnerable to capture. Specifically, traits related to energy balance (e.g., metabolic rate), swimming performance (e.g., aerobic scope), neuroendocrinology (e.g., stress responsiveness) and sensory physiology (e.g., visual acuity) are especially likely to influence vulnerability to capture through a variety of mechanisms. Selection on these traits could produce major shifts in the physiological traits within populations in response to fishing pressure that are yet to be considered but which could influence population resource requirements, resilience, species’ distributions and responses to environmental change.

Animal tracking data are being collected more frequently, in greater detail, and on smaller taxa than ever before. These data hold the promise to increase the relevance of animal movement for understanding ecological processes, but this potential will only be fully realized if their accompanying location error is properly addressed. Historically, coarsely-sampled movement data have proved invaluable for understanding large scale processes (e.g., home range, habitat selection, etc.), but modern fine-scale data promise to unlock far more ecological information. While location error can often be ignored in coarsely sampled data, fine-scale data require much more care, and tools to do this have been lacking. Current approaches to dealing with location error largely fall into two categories—either discarding the least accurate location estimates prior to analysis or simultaneously fitting movement and error parameters in a hidden-state model. Unfortunately, both of these approaches have serious flaws. Here, we provide a general framework to account for location error in the analysis of animal tracking data, so that their potential can be unlocked. We apply our error-model-selection framework to 190 GPS, cellular, and acoustic devices representing 27 models from 14 manufacturers. Collectively, these devices are used to track a wide range of animal species comprising birds, fish, reptiles, and mammals of different sizes and with different behaviors, in urban, suburban, and wild settings. Then, using empirical data on tracked individuals from multiple species, we provide an overview of modern, error-informed movement analyses, including continuous-time path reconstruction, home-range distribution, home-range overlap, speed and distance estimation. Adding to these techniques, we introduce new error-informed estimators for outlier detection and autocorrelation visualization. We furthermore demonstrate how error-informed analyses on calibrated tracking data can be necessary to ensure that estimates are accurate and insensitive to location error, and allow researchers to use all of their data. Because error-induced biases depend on so many factors—sampling schedule, movement characteristics, tracking device, habitat, etc.—differential bias can easily confound biological inference and lead researchers to draw false conclusions.

Summary A phenotypic syndrome refers to complex patterns of integration among functionally related traits in an organism that defines how the organism interacts with its environment and sustains itself. Human‐induced biological invasions have become important sources of environmental modifications. However, the extent to which invasive species affect the phenotypic syndromes of individuals in a native is currently unknown. Such knowledge has important implications for understanding ecological interactions and the management of biological invasions. Here, field monitoring in a natural stream were combined with standardized estimates of behavioral, physiological and morphological traits to address the hypothesis that coexistence with a non‐native invader induces a novel environmental pressure that disrupts the adaptive integration among phenotypic traits of the native species. We compared the strength of integration among key phenotypic traits (i.e. aerobic scope, standard metabolic rate, body growth, activity, and body shape) and ecological niche traits (i.e. spring and summer diet, home range size, daily movements) of an allopatric group of native brown trout (Salmo trutta) with a group of brown trout living in sympatry with non‐native brook trout (Salvelinus fontinalis). We found that the integration of phenotypic traits was substantially reduced in the sympatric brown trout and that allopatric and sympatric brown trout differed in key phenotypic and ecological niche traits. Brown trout living in sympatry with non‐native brook trout consumed more terrestrial prey, had smaller home ranges, and a stouter body shape. Sympatric brown trout also had lower specific growth rate, suggesting a lower fitness. The results are generally in line with our hypothesis suggesting that the reduction in fitness observed in sympatric brown trout is caused by the breakdown of their adaptive phenotypic syndrome. This may be caused by differences in the plasticity of the response of phenotypic traits to the novel selection pressure induced by the non‐native species. Our results may help explaining deleterious effects of non‐native species reported in the absence of direct competition with the native species. A http://onlinelibrary.wiley.com/doi/10.1111/1365-2435.12862/suppinfo is available for this article.

Selection induced by human harvest can lead to different patterns of phenotypic change than selection induced by natural predation and could be a major driving force of evolution of wild populations. The vulnerability of individuals to angling depends on the individual decision to ingest the bait, possibly mediated by their neuroendocrine response towards the associated stimulus. To investigate the mechanisms behind individual vulnerability to angling, we conducted angling experiments in replicated ponds and quantified individual behavioral traits and neuroendocrine stress responsiveness in two salmonid species, rainbow trout (Oncorhynchus mykiss) and brown trout (Salmo trutta). We discovered a phenotypic syndrome in rainbow trout, but not in brown trout, where lower serotonergic and dopaminergic brain activity and cortisol levels (i.e., lower stress responsiveness) in response to a standardized experimental stressor were associated with higher activity, forming a proactive phenotype that showed increased vulnerability to angling. Our results show that angling targets the most stress-resilient and active phenotypes of rainbow trout, supporting the suggestion that fishing-induced phenotypic selection may lead to an increased representation of stress-responsive and low-activity phenotypes in harvested populations.