Capability of movementfeatures extracted fromGPS trajectoriesforthe classification of fine‐grained behaviors

Ponencias, comunicaciones y pósters presentados en el 17th AGILE Conference on Geographic Information Science "Connecting a Digital Europe through Location and Place", celebrado en la Universitat Jaume I del 3 al 6 de junio de 2014.Recent advances in tracking technologies provide an unprecedented opportunity for a better understanding of animal movement. Data from multiple sensors can be used to capture crucial factors deriving the behaviors of the animal. Typically, accelerometer data is used to describe and classify fine-grained behaviors, while GPS data are rather used to identify more large-scale mobility patterns. In this study, however, the main research question was to what extent fine-grained foraging behaviors of wading birds can be classified from GPS tracking data alone. The species used in this study was the Eurasian Oystercatcher, Haematopus ostralegus. First, a supervised classification approach is employed based on parameters extracted from accelerometer data to identify and label different behavioral categories. Then, we seek to establish how movement parameters, computed from GPS trajectories, can identify the previously labeled behaviors. A decision tree was developed to see which movement features specifically contribute to predicting foraging. The methods used in this study suggest that it is possible to extract, with high accuracy, fine-grained behaviors based on high-resolution GPS data, providing an opportunity to build a prediction model in cases where no additional sensor or observational data on behavior is available. The key to success, however, is a careful selection of the movement features used in the classification process, including cross-scale analysis

Physics-informed inference of aerial animal movements from weather radar data

Studying animal movements is essential for effective wildlife conservation and conflict mitigation. For aerial movements, operational weather radars have become an indispensable data source in this respect. However, partial measurements, incomplete spatial coverage, and poor understanding of animal behaviours make it difficult to reconstruct complete spatio-temporal movement patterns from available radar data. We tackle this inverse problem by learning a mapping from high-dimensional radar measurements to low-dimensional latent representations using a convolutional encoder. Under the assumption that the latent system dynamics are well approximated by a locally linear Gaussian transition model, we perform efficient posterior estimation using the classical Kalman smoother. A convolutional decoder maps the inferred latent system states back to the physical space in which the known radar observation model can be applied, enabling fully unsupervised training. To encourage physical consistency, we additionally introduce a physics-informed loss term that leverages known mass conservation constraints. Our experiments on synthetic radar data show promising results in terms of reconstruction quality and data-efficiency.Comment: NeurIPS 2022, AI4Science worksho

A multidisciplinary study of an exceptional prehistoric waste dump in the mountainous inland of Calabria (Italy) : implications for reconstructions of prehistoric land use and vegetation in Southern Italy

The mountainous inland of northern Calabria (Southern Italy) is known for its sparse prehistoric human occupation. Nevertheless, a thorough multidisciplinary approach of field walking, geophysical survey and invasive research led to the discovery of a major archaeological archive. This archive concerns a rich multi-phased dump, spanning about 3000 years (Late Neolithic to Late Imperial Roman Age) and holding two Somma-Vesuvius tephra. Of these, the younger is a distinct layer of juvenile tephra from the Pompeii eruption, while the older concerns reworked tephra from the Bronze Age AP2 eruption (ca. 1700 cal. yr BP). The large dump contains abundant ceramics, faunal remains and charcoal, and most probably originated through long-continued deposition of waste in a former gully like system of depressions. This resulted in an inversed, mound-like relief, whose anthropogenic origin had not been recognized in earlier research. The tephras were found to be important markers that support the reconstruction of the occupational history of the site. The sequence of occupational phases is very similar to that observed in a recent palaeoecological study from nearby situated former lakes (Lago Forano/Fontana Manca). This suggests that this sequence reflects the more regional occupational history of Calabria, which goes back to ca. 3000 BC. Attention is paid to the potential link between this history and Holocene climatic phases, for which no indication was found. The history deviates strongly from histories deduced from the few, but major palaeorecords elsewhere in the inlands of Southern Italy (Lago Grande di Monticchio and Lago Trifoglietti). We conclude that major regional variation occurred in prehistoric land use and its impacts on the vegetation cover of Southern Italy, and studies of additional palaeoarchives are needed to unravel this complex history. Finally, shortcomings of archaeological predictive models are discussed and the advantages of truly integrated multidisciplinary research

Balancing food and density-dependence in the spatial distribution of an interference-prone forager

Foraging distributions are thought to be density-dependent, because animals not only select for a high availability and quality of resources, but also avoid conspecific interference. Since these processes are confounded, their relative importance in shaping foraging distributions remains poorly understood. Here we aimed to rank the contribution of density-dependent and density-independent effects on the spatio-temporal foraging patterns of eurasian oystercatchers. In our intertidal study area, tides caused continuous variation in oystercatcher density, providing an opportunity to disentangle conspecific interference and density-independent interactions with the food landscape. Spatial distributions were quantified using high-resolution individual tracking of foraging activity and location. In a model environment that included a realistic reconstruction of both the tides and the benthic food, we tested a family of behaviour-based optimality models against these tracking data. Density-independent interactions affected spatial distributions much more strongly than conspecific interference, even in an interference-prone species like oystercatchers. Spatial distributions were governed by avoidance of bill injury costs, selection for high interference-free intake rates and a decreasing availability of benthic bivalve prey after their exposure. These density-independent interactions outweighed interference competition in terms of effect size. We suggest that the bottleneck in our mechanistic understanding of foraging distributions may be primarily the role of density-independent prey attributes unrelated to intake rates, like damage costs in the case of oystercatchers foraging on perilous prey. At a landscape scale, above the finest inter-individual distances, effects of conspecific interaction on spatial distributions may have been overemphasised

The long-term fate of deposited nitrogen in temperate forest soils

Increased anthropogenic nitrogen (N) inputs can alter the N cycle and affect forest ecosystem functions. The impact of increased N deposition depends among others on the ultimate fate of N in plant and soil N pools. Short-term studies (3-18 months) have shown that the organic soil layer was the dominant sink for N. However, longer time scales are needed to investigate the long-term fate of N. Therefore, the soils of four experimental forest sites across Europe were re-sampled similar to 2 decades after labelling with(15)N. The sites covered a wide range of ambient N deposition varying from 13 to 58 kg N ha(-1)year(-1). To investigate the effects of different N loads on(15)N recovery, ambient N levels were experimentally increased or decreased. We hypothesized that: (1) the mineral soil would become the dominant(15)N sink after 2 decades, (2) long-term increased N deposition would lead to lower(15)N recovery levels in the soil and (3) variables related to C dynamics would have the largest impact on(15)N recovery in the soil. The results show that large amounts of the added(15)N remain in the soil after 2 decades and at 2 out of 4 sites the(15)N recovery levels are higher in the mineral soil than in the organic soil. The results show no clear responses of the isotopic signature to the changes in N deposition. Several environmental drivers are identified as controlling factors for long-term(15)N recovery. Most drivers that significantly contribute to(15)N recovery are strongly related to the soil organic matter (SOM) content. These findings are consistent with the idea that much of the added(15)N is immobilized in the SOM. In the organic soil layer, we identify C stock, thickness of the organic layer, N-status and mean annual temperature of the forest sites as most important controlling factors. In the mineral soil we identify C stock, C content, pH, moisture content, bulk density, temperature, precipitation and forest stand age as most important controlling factors. Overall, our results show that these temperate forests are capable of retaining long-term increased N inputs preferably when SOM availability is high and SOM turnover and N availability are low.publishedVersio

Long-distance migrants vary migratory behaviour as much as short-distance migrants : an individual-level comparison from a seabird species with diverse migration strategies

As environmental conditions fluctuate across years, seasonal migrants must determine where and when to move without comprehensive knowledge of conditions beyond their current location. Animals can address this challenge by following cues in their local environment to vary behaviour in response to current conditions, or by moving based on learned or inherited experience of past conditions resulting in fixed behaviour across years. It is often claimed that long-distance migrants are more fixed in their migratory behaviour because as distance between breeding and wintering areas increases, reliability of cues to predict distant and future conditions decreases. While supported by some population-level studies, the influence of migration distance on behavioural variation is seldom examined on an individual level. Lesser black-backed gulls Larus fuscus are generalist seabirds that use a diversity of migration strategies. Using high-resolution multi-year GPS tracking data from 82 individuals from eight colonies in Western Europe, we quantified inter- and intra-individual variation in non-breeding distributions, winter site fidelity, migration routes and timing of migration, with the objectives of determining how much variation lesser black-backed gulls have in their migratory behaviour and examining whether variation changes with migration distance. We found that intra-individual variation was significantly lower than variation between individuals for non-breeding distributions, winter site fidelity, migration routes and timing of migration, resulting in consistent individual strategies for all behaviours examined. Yet, intra-individual variation ranged widely among individuals (e.g. winter site overlap: 0-0.91 out of 1; migration timing: 0-192 days), and importantly, individual differences in variation were not related to migration distance. The apparent preference for maintaining a consistent strategy, present in even the shortest distance migrants, suggests that familiarity may be more advantageous than exactly tracking current environmental conditions. Yet, variation in behaviour across years was observed in many individuals and could be substantial. This suggests that individuals, irrespective of migration distance, have the capacity to adjust to current conditions within the broad confines of their individual strategies, and occasionally, even change their strategy

Music production and its role in coalition signaling during foraging contexts in a hunter-gatherer society

Music is a cultural activity universally present in all human societies. Several hypotheses have been formulated to understand the possible origins of music and the reasons for its emergence. Here, we test two hypotheses: (1) the coalition signaling hypothesis which posits that music could have emerged as a tool to signal cooperative intent and signal strength of alliances and (2) music as a strategy to deter potential predators. In addition, we further explore the link between tactile cues and the propensity of mothers to sing toward infants. For this, we investigated the singing behaviors of hunter-gatherer mothers during daily foraging trips among the Mbendjele BaYaka in the Republic of the Congo. Although singing is a significant component of their daily activities, such as when walking in the forest or collecting food sources, studies on human music production in hunter-gatherer societies are mostly conducted during their ritual ceremonies. In this study, we collected foraging and singing behavioral data of mothers by using focal follows of five BaYaka women during their foraging trips in the forest. In accordance with our predictions for the coalition signaling hypothesis, women were more likely to sing when present in large groups, especially when group members were less familiar. However, predictions of the predation deterrence hypothesis were not supported as the interaction between group size and distance from the village did not have a significant effect on the likelihood of singing. The latter may be due to limited variation in predation risk in the foraging areas, because of the intense bush meat trade, and hence, future studies should include foraging areas with higher densities of wild animals. Lastly, we found that mothers were more likely to sing when they were carrying infants compared to when infants were close, but carried by others, supporting the prediction that touch plays an important prerequisite role in musical interaction between the mother and child. Our study provides important insight into the role of music as a tool in displaying the intent between or within groups to strengthen potentially conflict-free alliances during joint foraging activities

Infrasound as a cue for seabird navigation

Seabirds are amongst the most mobile of all animal species and spend large amounts of their lives at sea. They cross vast areas of ocean that appear superficially featureless, and our understanding of the mechanisms that they use for navigation remains incomplete, especially in terms of available cues. In particular, several large-scale navigational tasks, such as homing across thousands of kilometers to breeding sites, are not fully explained by visual, olfactory or magnetic stimuli. Low-frequency inaudible sound, i.e., infrasound, is ubiquitous in the marine environment. The spatio-temporal consistency of some components of the infrasonic wavefield, and the sensitivity of certain bird species to infrasonic stimuli, suggests that infrasound may provide additional cues for seabirds to navigate, but this remains untested. Here, we propose a framework to explore the importance of infrasound for navigation. We present key concepts regarding the physics of infrasound and review the physiological mechanisms through which infrasound may be detected and used. Next, we propose three hypotheses detailing how seabirds could use information provided by different infrasound sources for navigation as an acoustic beacon, landmark, or gradient. Finally, we reflect on strengths and limitations of our proposed hypotheses, and discuss several directions for future work. In particular, we suggest that hypotheses may be best tested by combining conceptual models of navigation with empirical data on seabird movements and in-situ infrasound measurements

From Sensor Data to Animal Behaviour: An Oystercatcher Example

Animal-borne sensors enable researchers to remotely track animals, their physiological state and body movements. Accelerometers, for example, have been used in several studies to measure body movement, posture, and energy expenditure, although predominantly in marine animals. In many studies, behaviour is often inferred from expert interpretation of sensor data and not validated with direct observations of the animal. The aim of this study was to derive models that could be used to classify oystercatcher (Haematopus ostralegus) behaviour based on sensor data. We measured the location, speed, and tri-axial acceleration of three oystercatchers using a flexible GPS tracking system and conducted simultaneous visual observations of the behaviour of these birds in their natural environment. We then used these data to develop three supervised classification trees of behaviour and finally applied one of the models to calculate time-activity budgets. The model based on accelerometer data developed to classify three behaviours (fly, terrestrial locomotion, and no movement) was much more accurate (cross-validation error = 0.14) than the model based on GPS-speed alone (cross-validation error = 0.35). The most parsimonious acceleration model designed to classify eight behaviours could distinguish five: fly, forage, body care, stand, and sit (cross-validation error = 0.28); other behaviours that were observed, such as aggression or handling of prey, could not be distinguished. Model limitations and potential improvements are discussed. The workflow design presented in this study can facilitate model development, be adapted to a wide range of species, and together with the appropriate measurements, can foster the study of behaviour and habitat use of free living animals throughout their annual routine