Animal Movement Research Articles

The hidden role of buffalo trade network in bovine epidemic spreading

Animal movements are a key factor in the spread of pathogens. Consequently, network analysis of animal movements is a well-developed and well-studied field. The relationships between animals facilitate the diffusion of infectious agents and, in particular, shared environments and close interactions can facilitate cross-species transmission. Cattle are often the focus of these studies since they are among the most widely distributed and traded species globally. This remains true for Italy as well, but with an important additional consideration. Indeed, another important productive reality in the peninsula is buffalo farming. These farms have an interesting characteristic: approximately two-thirds of them also rear cattle. This coexistence between cattle and buffalo could have an impact on the diffusion of pathogens. Given that buffalo farms are often overlooked in the literature, the primary goal of this work is to investigate the potential consequences of omitting buffalo from cattle network analyses. To investigate this impact, we will focus on Q fever, a disease that can infect both species and is present on the Italian territory and for which the impact of the buffalo population has not been thoroughly studied, and simulate its spread to the farms of both species through compartmental models. Our analysis reveals that despite the significant difference in network sizes, the unique characteristic of Italian buffalo farms makes the buffalo network essential for a comprehensive understanding of bovine disease dynamics in Italy.

Speed and Shape of Population Fronts with Density-Dependent Diffusion

There is growing empirical evidence that animal movement patterns depend on population density. We investigate travelling wave solutions in reaction-diffusion models of animal range expansion in the case that population diffusion is density-dependent. We find that the speed of the selected wave depends critically on the strength of diffusion at low density. For sufficiently large low-density diffusion, the wave propagates at a speed predicted by a simple linear analysis. For small or zero low-density diffusion, the linear analysis is not sufficient, but a variational approach yields exact or approximate expressions for the speed and shape of population fronts.

A network evaluation of human and animal movement data across multiple swine farm systems in North America

INTRODUCTIONThe U.S. swine industry is vulnerable to the rapid spread of disease due to systemic structural issues. While animal movement networks are used to identify disease spread risks and design response plans, human movement between farms were rarely accounted for. Human movements, when integrated with animal movement models, create a different, more inclusive, and accurate network structure when compared to animal movements alone. METHODSOne year of propriety farm visit data was analyzed and consisted of anonymized property IDs, location, and user/truck IDs, along with visit dates, property, vehicle, and entry types from three swine management companies. A static directed network was created using the igraph package in R for all movements, with separate sub-networks for each entry type (animal, human, and subsets of vehicle types). Network statistics for each sub-network were compared. RESULTSThe full network included 455 properties, 11 property types, 9 vehicle types, 12 entry types, and 320001 edges (trips between properties). The longest path length was 10 in the animal movement network but decreased to 5 for the full and human movement network, while the average path length decreased from 3.2 to 2.2. Edge density increased from 0.03 to 0.09 for the human network and 0.1 for the full network. For all network properties examined, the full and human movement networks demonstrated higher connectivity than the animal network. A heavy right skew in the degree distributions indicates a 'hub' structure (scale-free-like network) and the shorter path lengths indicates a small-world network topology. DISCUSSIONThe full network is very well connected, more so than expected based on animal movement alone. Hubs may indicate points of disease susceptibility and 'super-spreader' properties. The high connectivity shows that swine farm networks may be more susceptible to spready of an introduced disease than expected from previous analyses. CONCLUSIONSMonitoring human, as well as animal movement, provides for a more complete and accurate understanding of swine farm biosecurity risks.

A Spatially‐Distributed Machine Learning Approach for Fractional Snow Covered Area Estimation

AbstractSnowpack in mountainous areas often provides water storage for summer and fall, especially in the Western United States. In situ observations of snow properties in mountainous terrain are limited by cost and effort, impacting both temporal and spatial sampling, while remote sensing estimates provide more complete spacetime coverage. Spatial estimates of fractional snow covered area (fSCA) at 30m are available every 16 days from the series of multispectral scanning instruments on Landsat platforms. Daily estimates at 463m spatial resolution are also available from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument on the Terra satellite. Fusing Landsat and MODIS fSCA images creates high resolution daily spatial estimates of fSCA that are needed for various uses: to support scientists and managers interested in energy and water budgets for water resources and to understand the movement of animals in a changing climate. Here, we propose a new machine learning approach conditioned on MODIS fSCA, as well as a set of physiographic features, and fit to Landsat fSCA over a portion of the Sierra Nevada USA. The predictions are daily 30m fSCA. The approach relies on two stages of spatially‐varying models. The first classifies fSCA into three categories and the second yields estimates within (0, 100) percent fSCA. Separate models are applied and fitted within sub‐regions of the study domain. Compared with a recently‐published machine learning model (Rittger, Krock, et al., 2021), this approach uses spatially local (rather than global) random forests, and improves the classification error of fSCA by 16%, and fractionally‐covered pixel estimates by 18%.

The gravity of Paleolithic hunting

Topographic relief potentially played an important role in Stone Age hunting from the Middle Paleolithic onwards. Natural physical features like arroyos and cliffs, among many others, likely served as traps to stop or hinder animal movement. Yet, the presence of elevation and slope variation on a landscape means that hunters also may have been able to use terrain to hunt from on high. Here, we explored via archaeological experiment how an elevated position would have interacted with projectile weaponry via the force of gravity to influence a missile’s functional efficacy. We assessed the velocity and kinetic impact energy of two Paleolithic projectile weapon systems, the thrown javelin and the atlatl (spearthrower) and dart, at ground level and then at three-, six-, and nine-meter launch heights. The experimental results of the javelin supported our predictions. Velocity and kinetic impact energy increased as launch height increased. Unexpectedly, however, atlatl-propelled darts did not conform to our predictions, not only failing to increase dart velocity or kinetic impact energy as launch height increased but also decreasing both variables’ values. These results suggest that Paleolithic hunting with an atlatl in certain contexts likely came with consequential, and previously undocumented, opportunity costs. Our results also have implications for several aspects of archaeological interpretation in Paleolithic and post-Paleolithic contexts.

Modeling the Impact of Short-Term Displacement of Domestic Animals on the Transmission Dynamics of Brucellosis

Brucellosis, a prevalent zoonotic disease caused by bacteria from the genus Brucella, presents a substantial public health and economic challenges worldwide. In this paper, we formulate a two-patch deterministic model to investigate the impact of short-term displacement of domestic animals on the transmission dynamics of brucellosis within and between patches with heterogeneous risk of infection. The model analysis is performed, and the basic reproduction number (R0) is computed and used in the stability analysis of equilibria. A global sensitivity analysis is performed using Latin Hypercube Sampling (LHS) approach to check the impact of model parameters over a period of time. Numerical simulation results indicate that the increase in time spent by domestic animals in high-risk areas, such as communal grazing areas or wildlife interfaces, significantly increases the spread of infections. This underscores the importance of considering short-term animal movements to communal grazing areas and water points in brucellosis management strategies. It equips policymakers and stakeholders with actionable insights to combat the burden of the disease.

Stable isotope analysis of faunal remains from Bronze Age Kaymakçı, Western Anatolia

This paper presents the results of stable carbon ( δ13C) and nitrogen ( δ15N) isotopic analysis of bulk bone collagen from faunal remains from the Bronze Age site of Kaymakçı in western Anatolia. We use the isotopic values in conjunction with zooarchaeological data and contextual archaeological information to examine human-environment interactions; in particular, animal management and husbandry. Middle and Late Bronze Age agricultural systems in western and central Anatolia remain poorly understood, and this research aims to contribute to rectifying this research gap. We obtained stable isotopic values from both wild and domestic species, including deer, hare, birds, catfish, dogs, pigs, caprids and cattle. The δ13C values range from −22.0‰ to −16.9‰ and the δ15N values range from 2.3‰ to 10.3‰. For cattle, the δ13C values suggest that some specimens were subject to different management strategies, likely related to feeding or herding patterns or even the movement of animals in and around the region through some exchange mechanism. There appears to be no fixed location or strategy for the management of caprids and, furthermore, there is evidence to suggest that the herding/management areas of some caprids overlapped with those of wild animals such as deer and hare. Variation in δ15N values for pigs may indicate that whilst some animals in the sampled assemblage were free-roaming, others were penned. For the pigs and some other herbivorous domesticated species variation in δ15N values may also point to the exploitation of the wetland areas around Lake Marmara.

Joint inference for telemetry and spatial survey data.

Data integration, the joint statistical analysis of data from different observation platforms, is pivotal for data-hungry disciplines such as spatial ecology. Pooled data types obtained from the same underlying process, analyzed jointly, can improve both precision and accuracy in models of species distributions and species-habitat associations. However, the integration of telemetry and spatial survey data has proved elusive because of the fundamentally different analytical approaches required by these two data types. Here, "spatial survey" denotes a survey that records spatial locations and has no temporal structure, for example, line or point transects but not capture-recapture or telemetry. Step selection functions (SSFs-the canonical framework for telemetry) and habitat selection functions (HSFs-the default approach to spatial surveys) differ in not only their specifications but also their results. By imposing the constraint that microscopic mechanisms (animal movement) must correctly scale up to macroscopic emergence (population distributions), a relationship can be written between SSFs and HSFs, leading to a joint likelihood using both datasets. We implement this approach using maximum likelihood, explore its estimation precision by systematic simulation, and seek to derive broad guidelines for effort allocation in the field. We find that complementarities in spatial coverage and resolution between telemetry and survey data often lead to marked inferential improvements in joint analyses over those using either data type alone. The optimal allocation of effort between the two methods (or the choice between them, if only one can be selected) depends on the overall effort expended and the pattern of environmental heterogeneity. Examining inferential performance over a broad range of scenarios for the relative cost between the two methods, we find that integrated analysis usually offers higher precision. Our methodological work shows how to integrate the analysis of telemetry and spatial survey data under a novel joint likelihood function, using traditional computational methods. Our simulation experiments suggest that even when the relative costs of the two methods favor the deployment of one field approach over another, their joint use is broadly preferable. Therefore, joint analysis of the two key methods used in spatial ecology is not only possible but also computationally efficient and statistically more powerful.

Flight power muscles have a coordinated, causal role in hawkmoth pitch turns.

Flying insects solve a daunting control problem of generating a patterned and precise motor program to stay airborne and generate agile maneuvers. In this motor program, each muscle encodes information about movement in precise spike timing down to the millisecond scale. Whereas individual muscles share information about movement, we do not know if they have separable effects on an animal's motion, or if muscles functionally interact such that the effects of any muscle's timing depend heavily on the state of the entire musculature. To answer these questions, we performed spike-resolution electromyography and electrical stimulation in the hawkmoth Manduca sexta during tethered flapping. We specifically explored how flight power muscles contribute to pitch control. Combining correlational study of visually-induced turns with causal manipulation of spike timing, we discovered likely coordination patterns for pitch turns, and investigated if these patterns can drive pitch control. We observed significant timing change of the main downstroke muscles, the dorsolongitudinal muscles (DLMs), associated with pitch turns. Causally inducing this timing change in the DLMs with electrical stimulation produced a consistent, mechanically relevant feature in pitch torque, establishing that power muscles in Manduca have a control role in pitch. Because changes were evoked in only the DLMs, however, these pitch torque features left large unexplained variation. We find this unexplained variation indicates significant functional overlap in pitch control such that precise timing of one power muscle does not produce a precise turn, demonstrating the importance of coordination across the entire motor program for flight.

Anxiolytic Efficacy of Indirubin: In Vivo Approach Along with Receptor Binding Profiling and Molecular Interaction with GABAergic Pathways.

Anxiety is a natural response to stress, characterized by feelings of worry, fear, or unease. The current research was conducted to investigate the anxiolytic effect of indirubin (IND) in different behavioral paradigms in Swiss albino mice. To observe the animal's behavioural response to assess anxiolytic activity, different tests were performed, such as the open-field (square cross, grooming, and rearing), swing, dark-light, and hole cross tests. The experimental mice were administered IND (5 and 10 mg/kg, p.o.), where diazepam (DZP) and vehicle were used as positive and negative controls, respectively. In addition, a combination treatment (DZP+IND-10) was provided to the animals to determine the modulatory effect of IND on DZP. Molecular docking approach was also conducted to determine the binding energy of IND with the GABAA receptor (α2 and α3 subunits) and pharmacokinetics were also estimated. The findings revealed that IND dose-dependently significantly (p<0.05) reduced the animal's movement exerting calming behavior like DZP. IND also demonstrated the highest docking score (-7.7 kcal/mol) against the α3 subunit, while DZP showed a lower docking value (-6.4 kcal/mol) than IND. The ADMET analysis revealed that IND has proper drug-likeness and pharmacokinetic characteristics. In conclusion, IND exerted anxiolytic effects through GABAergic Pathways.

AUTOMATED TECHNOLOGY OF MEASUREMENT OF PHYSIOLOGICAL PARAMETERS OF FARM ANIMALS

Abstract. The development and application of automated technologies in the agricultural sector have significantly transformed the management and monitoring of farm animals. This paper presents a comprehensive analysis of existing technical systems for measuring the physiological parameters of farm animals, particularly focusing on cows. The primary goal of these technologies is to enhance the accuracy and efficiency of health monitoring and to optimize livestock management through continuous data collection and analysis. Key technological solutions include the use of wireless data transmission systems, radio monitoring devices, and unmanned aerial vehicles (UAVs). These technologies enable real-time tracking of animal health parameters such as body temperature, heart rate, movement patterns, and other critical indicators. The use of various sensors, including ear, neck, and intra-body sensors, plays a crucial role in collecting primary physiological data. These sensors are integrated into a broader system that includes radio modules with built-in controllers for converting raw data into digital formats, enabling wireless transmission to central systems for processing and storage. The radio monitoring of animals allows for the continuous tracking of physiological and behavioral parameters across large areas, providing crucial insights into their well-being. It is particularly beneficial in detecting early signs of disease or health issues, ensuring timely intervention, and preventing potential economic losses for farmers. The integration of unmanned aerial vehicles (UAVs) further expands the capabilities of monitoring systems, enabling the visual assessment of animals' behavior and movement across vast pastures. Equipped with video cameras and data relays, UAVs collect video footage that is transmitted to a central processing unit for real-time analysis and storage. The combined use of radio monitoring and UAV technology forms a comprehensive framework for livestock management, allowing farmers to make data-driven decisions, optimize resource allocation, and improve overall herd health and productivity. By leveraging these automated systems, it becomes possible to reduce the dependency on manual labor, minimize human error, and ensure that animals are closely monitored without the need for constant physical presence. This represents a significant advancement in modern animal farming, aligning with global trends toward smart farming and precision agriculture. In conclusion, the integration of automated physiological monitoring technologies in farm animal management presents an innovative solution for enhancing animal welfare, improving farm efficiency, and reducing operational costs. These systems hold considerable potential for further advancements in the field of animal health monitoring, ultimately contributing to more sustainable and productive farming practices.

Multiphasic movement and step-selection patterns of dispersed tigers in the central Indian landscape.

Large carnivores play a crucial role in the ecosystem, though their conservation needs a landscape-level approach due to their wide range of habitats and dispersal events. The study of tigers in a human-dominated landscape matrix and their adaptation and adjustment of movement behaviours during the dispersal phase is essential for long-term conservation planning and management policy. We studied the dispersal event of five VHF/GPS collared individuals during 2009-2020. We investigated movement parameters (step length), and the effects of anthropogenic pressures (distance from village), distance from water and vegetation cover, on behavioural phase under a Hidden Markov Model framework. We also tested the effects of distance from village, vegetation cover, and habitat types on animal movement using an integrated Step Selection Function framework. The mean step length (405.44±10.63 m/hr) varied widely by different time of day. Displacement was high during the night (665.28±21.36 m/hr) compared to day (434.16±17.37 m/hr). Tigers moved fast (872.7m; 95% CI 839.1-906.3m) with longer step length and a directional turning angle in non-forested areas (i.e. the human-dominated landscape), likely to avoid conflict with humans. Individuals distinctly exhibited two behavioural states: encamping (~32% of the time) and travelling (~68% of the time). Further, they avoided the human-dominated landscape and mostly remained in and forested areas, especially during nighttime. Our study is the first attempt to understand behavioural transition of dispersal tigers and their habitat selection. Lesser anthropogenic disturbance and high vegetation cover positively influenced the tiger dispersal, while water availability did not affect their state transitional probability. Additionally, dispersers showed high affinity towards forested land during nighttime for travelling.The findings of this study show the importance of functional corridors and stepping stones (mostly encamping areas), and also provide baseline knowledge for integrated landscape management planning and policymaking for the long-term survival of tigers in metapopulation framework.

An individual‐based model trained on multiple data sources estimates population connectivity and facilitates aggregation of harvest management units

Abstract Management boundaries are often delimited by political and social factors, whereas animal movements are affected by ecological and geophysical constraints. Thus, understanding connectivity among distinct management units is of considerable importance, particularly for harvested species, where quotas set in ignorance of connectivity may fail to meet management goals. We constructed an individual‐based model (IBM) to better understand wild turkey movements at large scales, benefiting from multiple data sources that are often available for harvested species. We built an IBM from spring seasonal movements of wild turkey, using data from ringed, radio‐, and GPS‐marked turkeys captured in Maine, USA. Our IBM accommodated variation in individual turkey response to landscape connectivity metrics and identified emergent migratory connectivity dynamics among harvest management regions. We calculated a low degree of connectivity among wildlife management districts (WMD) which, in combination with the substantial number of boundary crossings observed, indicated a more diffuse distribution of turkeys among WMDs. Synthesis and applications: Estimates of turkeys moving between districts provided a clear delineation of where immigration was strongest, identifying which WMDs should be managed as singular population units. This approach has widespread utility for any species or system where harvest management decisions are made at finer spatial scales than the movement dynamics affecting population processes.

Using GPS and accelerometer data to remotely detect breeding events in two elusive ground-nesting steppe birds

BackgroundModern biologging technologies allow researchers to gain a better understanding of animal movements, offering opportunities to measure survival and remotely study the breeding success of wild birds, i.e., by locating nests. This is particularly useful for species whose nests are difficult to find or access, or when disturbances can impact the breeding outcome. We developed and validated, with field data, a framework to detect nesting events by two sandgrouse species, the black-bellied (Pterocles orientalis) and pin-tailed sandgrouse (Pterocles alchata), using GPS and Overall Dynamic Body Acceleration (ODBA) data. Sandgrouses are ground-nesting, cryptic, and elusive birds with biparental incubation efforts. Because both sexes take turns to incubate, a novel framework considering when tagged individuals are on incubation duty or not needs to be designed to detect nests.ResultsWe tagged 52 birds with high-resolution GPS devices to monitor their breeding during 2021–24. Using remote tracking and field data from the first 2 years (2021–22), we first determined sex-specific time windows for incubation to maximise differentiation between incubation and non-incubation behaviours. We then used a threshold-based classification to identify incubation days and inferred the minimum number of successive incubation days needed to correctly identify a nesting event. We show how ODBA and GPS data can be used to successfully detect nests incubated for only 2 or 3 days. GPS-only data or combined GPS-ODBA data had a success rate of around 95%, whereas ODBA-only data had a success rate of 100%. Cross-validation using data from 2023 to 2024 confirmed the model’s performance, showing an overall success > 90% for GPS-only and ODBA-only data and of 85% for combined GPS–ODBA data.ConclusionsBy accurately identifying nesting events, our framework offers new opportunities to study the breeding of conservation-dependent species. Besides its applicability to ground-nesting species with biparental care and sex-specific incubation schedules, the framework can be adapted to other bird species sensitive to disturbances or with inaccessible nesting sites. By doing so, it reduces the need for nest visits and associated disturbances, as well as the carbon footprint and expenses associated with fieldwork.

Three-dimensional vegetation structure drives patterns of seed dispersal by African hornbills.

Three-dimensional (3D) vegetation structure influences animal movements and, consequently, ecosystem functions. Animals disperse the seeds of 60%-90% of trees in tropical rainforests, which are among the most structurally complex ecosystems on Earth. Here, we investigated how 3D rainforest structure influences the movements of large, frugivorous birds and resulting spatial patterns of seed dispersal. We GPS-tracked white-thighed (Bycanistes albotibialis) and black-casqued hornbills (Ceratogymna atrata) in a study area surveyed by light detection and ranging (LiDAR) in southern Cameroon. We found that both species preferred areas of greater canopy height and white-thighed hornbill preferred areas of greater vertical complexity. In addition, 33% of the hornbills preferred areas close to canopy gaps, while 16.7% and 27.8% avoided large and small gaps, respectively. White-thighed hornbills avoided swamp habitats, while black-casqued increased their preference for swamps during the hottest temperatures. We mapped spatial probabilities of seed dispersal by hornbills, showing that 3D structural attributes shape this ecological process by influencing hornbill behaviour. These results provide evidence of a possible feedback loop between rainforest vegetation structure and seed dispersal by animals. Interactions between seed dispersers and vegetation structure described here are essential for understanding ecosystem functions in tropical rainforests and critical for predicting how rainforests respond to anthropogenic impacts.

Mechanisms of memory-supporting neuronal dynamics in hippocampal area CA3.

Hippocampal CA3 is central to memory formation and retrieval. Although various network mechanisms have been proposed, direct evidence is lacking. Using intracellular Vm recordings and optogenetic manipulations in behaving mice, we found that CA3 place-field activity is produced by a symmetric form of behavioral timescale synaptic plasticity (BTSP) at recurrent synapses among CA3 pyramidal neurons but not at synapses from the dentate gyrus (DG). Additional manipulations revealed that excitatory input from the entorhinal cortex (EC) but not the DG was required to update place cell activity based on the animal's movement. These data were captured by a computational model that used BTSP and an external updating input to produce attractor dynamics under online learning conditions. Theoretical analyses further highlight the superior memory storage capacity of such networks, especially when dealing with correlated input patterns. This evidence elucidates the cellular and circuit mechanisms of learning and memory formation in the hippocampus.

Accounting for impairment, estimated liabilities and valuation of growing and fattening animals

In the context of digitalization of the agricultural economy, issues of automation of accounting of animals for growing and fattening in the digital accounting of agricultural organizations are becoming relevant. In addition, these organizations must keep records of animals for growing and fattening according to the requirements of new regulatory documents. In this regard, the article defines the tasks of accounting for animals for growing and fattening, provides the procedure for assessing the offspring and gain of animals, as well as animals acquired from outside by purchase, gratuitous receipt, receipt on account of a contribution to a mutual fund, received under contracts providing for the fulfillment of obligations (payment) by non-cash funds. The article proposes valuation of animals for growing and fattening at fair value, taking into account their qualitative characteristics. The methodology for accounting for animals for growing and fattening in accounts at fair value is given. Recommendations have been developed for valuation of animals for growing and fattening after their recognition in accounting, as well as accounting for the impairment of animals for growing and fattening and the creation of an estimated liability for them. The digitalization of operations for the movement of animals during rearing and fattening with full automation of their accounting is proposed

What Is the Work of Animation? The Plasticity of Time in the Fourth-Dimensional Image

Plasticity is a central concept in the philosophy of Catherine Malabou and the theory of animation. And yet, the temporal dimension of transformation and mutability that Malabou foregrounds in her philosophy is missing from recent theoretical accounts of plasticity in animation studies​. ​In these accounts, plasticity appears as a mode of spatial extension, conveying the elasticity of form across a Cartesian timeline, whereas Malabou aims to understand time’s own metamorphosis and self-differentiation. This article invokes Malabou’s theorization of plasticity as the becoming of time itself rather than the becoming of things in time to rethink the perception of life-like movement in animation. Reviewing the techniques of animation that Frank Thomas and Ollie Johnston describes in The Illusion of Life as “drawing in the fourth dimension”, I argue that Malabou’s characterization of plasticity as the capacity “to see (what is) coming” ( voir venir) gets to the heart of animation as an art of subjective anticipation. Utilizing the human perceptual system’s tendency to invent new structures and relationships in response to changing inputs from the environment, animation prepares us to anticipate the unforeseeable and to perceive an order of movement typically concealed by the movement of objects in space.

Challenges and opportunities when studying movement ecology in science and practical conservation

Movement is a key mechanism influencing biodiversity patterns and ecosystem processes. Movement ecology science aims to understand the causal relationships between environmental conditions, animal movements, interactions and coexistence of species, as well as effects of movement patterns on ecosystem processes. In contrast, practical conservation primarily aims to understand organisms' movements to improve species management, protection, legal monitoring or risk assessment, and species-habitat interactions. Despite the many studies of movement ecology in basic and applied sciences as well as in practical conservation in terrestrial ecosystems, knowledge gain and transfer between disciplines are limited. Better integration and linking of both disciplines would result in diverse science-practice synergies, but these are currently constrained by numerous challenges that need to be overcome. From a scientific perspective, knowledge gain from practice is limited by multitude of case studies with limited spatial and temporal resolution. This can be overcome by improving access and combining the diversity of data for a research area that often deals with small sample sizes. From a practical perspective, the movement ecology framework which is often dedicated to basic research, and access and language barriers of scientific publications limit the application of scientific results in practice. Here movement ecologists should be encouraged to consider conservation issues more frequently in addition to basic research. The transfer of scientific results could be improved by scientists providing sufficient details for practitioners to extract relevant information and publish at least an open-access abstract in local language with clear management recommendations. Further, the use of open-access repositories allows both, scientists and practitioners an overview of the multitude of studies and helps to share data in order to derive general conclusions. Challenges impacting science and practice can be conceptual, organisational and technical in nature. Such constrains can be overcome, for example, by providing verified trapping protocols, using recent technological developments and analytical methods combined with trainings on these state-of-the-art tracking and analysing tools. In particular, collaborative project planning between scientists and practitioners can help to improve the sampling design of applied studies and broaden the data base for science in order to significantly advance the movement ecology framework and gain comprehensive knowledge for practical conservation.

Tracking Small Animals in Complex Landscapes: AComparison of Localisation Workflows for Automated Radio Telemetry Systems.

Automated radio telemetry systems (ARTS) have the potential to revolutionise our understanding of animal movement by providing a near-continuous record of individual locations in the wild. However, localisation errors in ARTS data can be very high, especially in natural landscapes with complex vegetation structure and topography. This curtails the research questions that may be addressed with this technology. We set up an ARTS grid in a valley with heterogeneous vegetation cover in the Colombian high Andes and applied an analytical pipeline to test the effectiveness of localisation methods. We performed calibration trials to simulate animal movement in high- or low-flight, or walking on the ground, and compared workflows with varying decisions related to signal cleaning, selection, smoothing, and interpretation, along with four multilateration approaches. We also quantified the influence of spatial features on the system's accuracy. Results showed large variation in localisation error, ranging between 0.4-43.4 m and 474-1929 m, depending on the localisation method used. We found that the selection of higher radio signal strengths and data smoothing based on the temporal autocorrelation are useful tools to improve accuracy. Moreover, terrain ruggedness, height of movement, vegetation type, and the location of animals inside or outside the grid area influence localisation error. In the case of our study system, thousands of location points were successfully estimated for two high-altitude hummingbird species that previously lacked movement data. Our case study on hummingbirds suggests ARTS grids can be used to estimate small animals' home ranges, associations with vegetation types, and seasonality in occurrence. We present a comparative localisation pipeline, highlighting the variety of possible decisions while processing radio signal data. Overall, this study provides guidance to improve the resolution of location estimates, broadening the application of this tracking technology in the study of the spatial ecology of wild populations.