bioRxiv Science⌕ Search

Biology subjects

Takeshige, S.

Publications and source records attributed to Takeshige, S..

2 recordsLinked to original sources

Structural characteristics of important daily movement corridors for waterbirds in urban areas: A case study on Black-headed Gulls

Landscape management facilitating animal movement is essential for sustaining urban wildlife populations and ecosystem services. Although linear vegetation corridors effectively conserve terrestrial animal movements, it remains unclear which landscape elements serve as pathways for aquatic organisms. Urban waterbirds frequently utilize rivers, but the specific characteristics that render certain river segments crucial as movement corridors have yet to be elucidated. This study aims to identify the characteristics of river segments functioning as critical corridors based on waterbird movement strategies. We tracked the movement behaviors of the Black-headed Gull (Chroicocephalus ridibundus), a river-dependent species in daily movements, and identified key movement corridors in highly urbanized Tokyo, Japan. Using GPS tracking data from gulls, we evaluated how river sinuosity and surrounding feature heights influenced tendencies to follow rivers across various temporal scales and perceptual ranges. Furthermore, we predicted and mapped these tendencies across individual river segments in central Tokyo. Gulls tended to fly along river segments with tall features during instantaneous to mid-term decision-making. In contrast, they utilized straight channels for long-term decisions. Although results varied slightly depending on the spatial scale they can perceive, this overarching trend remained consistent. Furthermore, our model predicted that the lower reaches of the Sumida River serve as critical movement corridors. This predictive tendency was also highly robust across all time scales. While straightened river segments with high feature heights may provide unsuitable habitats for diverse taxa, we emphasize their ecological value and argue that they should be conserved as essential movement corridors for waterbirds.

ecology↗

Multiple imputation step-selection analysis: Improving estimation accuracy of travel distance accounting for route uncertainty

O_LIUnderstanding animal movement behavior is essential for conservation and elucidating various ecological processes. In particular, assessing habitat suitability is a central theme in movement ecology, traditionally evaluated by estimating travel distances per unit time across diverse environmental conditions based on tracking data. Integrated step selection analysis (iSSA : Avgar et al., 2016) has been most widely applied in conservation studies to estimate animal movements that provide ecosystem services due to its ease of implementation and interpretability. C_LIO_LIBut despite its popularity, iSSA faces a critical issue--it can lead to underestimation of cumulative travel distances because it measures step lengths as conventional straight-line displacements between locations. This is primarily due to the application of linear interpolation between consecutive observed points, which fails to account for unobserved occurrences and non-linear trajectories taken by the individual. C_LIO_LIIn this paper, we propose a novel method to improve the estimation of travel distance in iSSA inspired by multiple imputation, a statistical method for missing data. We tested the extent to which our proposed method, Multiple Imputation Step Selection Analysis (MiSSA), improves the accuracy of step-length estimation (parameters of gamma distribution) compared to conventional iSSA using simulations across various scenarios. We compared the estimation bias and error under landscapes with different spatial autocorrelations (Simulation 1), as well as under various combinations of movement and habitat selection parameters (Simulation 2). In all simulations, MiSSA successfully reduced the estimation bias of the step length and substantially improved the estimation accuracy. In addition, although the coverage rates were comparable, we achieved a substantial reduction in the width of the confidence intervals. C_LIO_LIOur study demonstrates that incorporating missing data statistics into the iSSA framework improves the accuracy of travel distance estimations, which serve as the foundation for evaluating habitat selection. MiSSA maintains the core advantages of iSSA while enabling more accurate estimation of travel distances, even for low-resolution data where movement between sampling intervals is non-linear. We anticipate its broad application across various disciplines, with a primary focus on conservation. C_LI

ecology↗