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The paradigm‐changing opportunities of biologging sensors for ecological research, especially movement ecology, are vast, but the crucial questions of how best to match the most appropriate sensors and sensor combinations to specific biological questions and how to analyse complex biologging data, are mostly ignored.Here, we fill this gap by reviewing how to optimize the use of biologging techniques to answer questions in movement ecology and synthesize this into an Integrated Biologging Framework (IBF).We highlight that multisensor approaches are a new frontier in biologging, while identifying current limitations and avenues for future development in sensor technology.We focus on the importance of efficient data exploration, and more advanced multidimensional visualization methods, combined with appropriate archiving and sharing approaches, to tackle the big data issues presented by biologging. We also discuss the challenges and opportunities in matching the peculiarities of specific sensor data to the statistical models used, highlighting at the same time the large advances which will be required in the latter to properly analyse biologging data.Taking advantage of the biologging revolution will require a large improvement in the theoretical and mathematical foundations of movement ecology, to include the rich set of high‐frequency multivariate data, which greatly expand the fundamentally limited and coarse data that could be collected using location‐only technology such as GPS. Equally important will be the establishment of multidisciplinary collaborations to catalyse the opportunities offered by current and future biologging technology. If this is achieved, clear potential exists for developing a vastly improved mechanistic understanding of animal movements and their roles in ecological processes and for building realistic predictive models. [ABSTRACT FROM AUTHOR]

Long‐term bio‐logging has the potential to reveal how movements, and hence life‐history trade‐offs, vary over a lifetime. Reproductive tactics in particular may vary as individuals' trade‐off current investment versus lifetime fitness. Male African savanna elephants (Loxodona africana) provide a telling example of balancing body growth with reproductive fitness due to the combination of indeterminate growth and strongly delineated periods of sexual activity (musth), which results in reproductive tactics that alter with age.Our study aims to quantify the extent to which male elephants alter their movement patterns, and hence energetic allocation, in relation to (a) reproductive state and (b) age, and (c) to determine whether musth periods can be detected directly from GPS tracking data.We used a combination of GPS tracking data and visual observations of 25 male elephants ranging in age from 20 to 52 years to examine the influence of reproductive state and age on movement. We then used a three‐state hidden Markov model (HMM) to detect musth behaviour in a subset of sequential tracking data.Our results demonstrate that male elephants increased their daily mean speed and range size with age and in musth. Furthermore, non‐musth speed decreased with age, presumably reflecting a shift towards energy acquisition during non‐musth. Thus, despite similar speeds and marginally larger ranges between reproductive states at age 20, by age 50, males were travelling 2.0 times faster in a 3.5 times larger area in musth relative to non‐musth. The distinctiveness of musth periods over age 35 meant the three‐state HMM could automatically detect musth movement with high sensitivity and specificity, but could not for the younger age class.We show that male elephants increased their energetic allocation into reproduction with age as the probability of reproductive success increases. Given that older male elephants tend to be both the target of legal trophy hunting and illegal poaching, man‐made interference could drive fundamental changes in elephant reproductive tactics. Bio‐logging, as our study reveals, has the potential both to quantify mature elephant reproductive tactics remotely and to be used to institute proactive management strategies around the reproductive behaviour of this charismatic keystone species. [ABSTRACT FROM AUTHOR]