Biology subjects

Benhamou, S.

Publications and source records attributed to Benhamou, S..

7 recordsLinked to original sources

bioRxiv2026

Spatial segregation and multi-scale space-use adjustments to socio-ecological variables in western gorillas

Background: Identifying the mechanisms that shape space-use dynamics and the scale at which they operate can provide insights into the socio-ecology of numerous animal species. This is crucial for addressing both applied (e.g., conservation) and theoretical questions (e.g., the coexistence or segregation of individuals). Yet, longitudinal views of the space-use dynamics are generally rare. Taking advantage of a long-term movement dataset (up to 8 years) on five habituated groups of wild western gorillas (Gorilla gorilla) in Central Africa, we investigated the dynamics of their space use in relation to the socio-ecological variables from everyday movement to home range shifts. Methods: We looked at which temporal scale their ranging movements are stationary to highlight the dynamics of home range settling and shifts. We also studied how daily space use is shaped by (i) foraging and intra-group constraints (i.e., diet, group size, presence of offspring), and by (ii) inter-group competition (direct or indirect), quantifying static and dynamic interactions in neighbouring group-dyads. Results: Gorilla groups shifted the centre of their home range 0.17 times per year by a distance larger than the mean home range radius. Movements within the home range were highly dependent on the group composition and the ecological features (with larger daily-travelled distances in the high-fruit season compared to the low-fruit season). The presence of dependent infants affected the daily-travel distance: the larger their number, the smaller the daily-travel distance. Furthermore, the frequently visited sites of the home range were also used the longest, but their locations differed seasonally, suggesting space use flexibility. Although there was little overlap between the home ranges of neighbouring groups, these groups did not seem to avoid each other more than expected at random. They could even venture into, and slept in, the central part of the home range of a neighbouring group. Conclusion: Our study suggests that spatial segregation should be the simple consequence of avoidance of depleted areas rather than of territorial behaviour. It shows how socio-ecological constraints may shape the space-use patterns at different scales in a non-territorial species, and questions the role of cognition in space-use dynamics.

ecology↗

bioRxiv2025

Deep Learning Bridges Histology and Transcriptomics to Predict Molecular Subtypes and Outcomes in Muscle-Invasive Bladder Cancer

Muscle-Invasive Bladder Cancer (MIBC) is a heterogeneous disease with distinct molecular subtypes influencing prognosis and therapeutic response. However, molecular profiling through RNA sequencing remains costly, time-consuming and complicated by intratumoral heterogeneity. We developed a Deep Learning (DL) approach to infer molecular subtypes from routine histopathological slides and to evaluate its prognostic value in patients treated with neoadjuvant chemotherapy (NAC). We developed an DL-model predicting the expression of 848 subtype-associated genes from histological images of transurethral resection of bladder tumor, enabling spatial molecular subtyping at tile level. The model was trained on 297 NAC-treated patients from the VESPER clinical trial and evaluated on three independent cohorts (COBLAnCE, n=224; Saint-Louis, n=30 and TCGA, n=315), covering diverse staining protocols and scanner types. Spatial transcriptomics from six VESPER patients confirmed the spatial consistency of the inferred expression profiles. Our approach achieved a ROC AUC of 0.94 for molecular subtype prediction, with 95% of genes significantly predicted, demonstrating its ability to capture transcriptomic dysregulations from histological morphology. Predicted expression maps revealed spatially coherent patterns and intratumoral molecular heterogeneity. Importantly, tumors predicted with basal/squamous features (pure or mixed), were associated with significantly worse progression-free and overall survival after NAC (log-rank p=0.014 and 0.037, respectively). This DL-based framework enables accurate and spatially resolved inference of gene expression and molecular subtypes in MIBC without sequencing. These findings could improve patient stratification in clinical practice and support the design of more targeted clinical trials. Further validation in larger cohorts is needed before routine clinical implementation.

cancer biology↗

bioRxiv2025

A simple method to classify behaviours of aerial predators using tri-axial high-frequency accelerometers

BackgroundRemote monitoring of animals has opened new avenues in behavioural research. The advent of animal-borne accelerometers makes it possible to derive the body posture and activity level, and thereby to identify fine-scale behaviours with no need for direct observation. This is particularly useful for species that forage or hunt beyond human sight in sometimes hard-to-access or remote areas. However, the complexity of numerous methods developed for this purpose may discourage researchers from effectively using acceleration data. ResultsWe present a simple and straightforward approach to identify and classify behaviours based on tri-axial high-frequency (25 Hz) acceleration data. This method relies on constructing a decision tree to assign predefined behaviours to time series of acceleration data using four accelerometer-based parameters that are biologically relevant and easy to interpret. Initially, we manually labelled sequences of acceleration data with the behaviours using paired high-frequency (i.e. 1 Hz) GPS tracking data as ground-truth. Then, threshold values of the acceleration-based parameters were objectively determined based on receiver operating characteristic (ROC) analysis. Finally, we built the decision tree to automatically classify the behaviours of the whole dataset and tested further improvements. As a case study, we used two falcon species (lesser kestrel Falco naumanni and common kestrel F. tinnunculus). Our simple method achieved an overall accuracy of 97.6% in classifying the following behaviours: perching (99.9%), soaring-gliding (99.3%), flapping (93.1%) and hovering (86.4%). We also showed that kestrels prey capture attempts can be identified from the tri-axial high-frequency accelerometers due to diagnostic signatures (the so-called spikes). ConclusionsOur simple method has broad applicability to free-ranging aerial predators. We show that behavioural categories can be accurately classified from a relatively small subset of manually labelled acceleration data (43,075 seconds). Although quantifying hunting success needs further investigation, the detection of prey capture attempts opens new possibilities for studying the hunting behaviour of aerial predators.

ecology↗

bioRxiv2022

Accounting for central place foraging constraints in habitat selection studies

Habitat selection studies contrast the actual space use with the expected use under the null hypothesis of no preference (hereafter neutral use). Neutral use is most often assimilated to the relative abundance of the different habitat types. This generates a considerable bias when studying habitat selection by foragers that perform numerous back and forth to a central place (CP). Indeed, the increased space use close to the CP with respect to distant places reflects a mechanical effect rather than a true preference for the closest habitats. Yet, correctly estimating habitat selection by CP foragers is of paramount importance for a better understanding of their ecology and efficiency of conservation actions. We show that (1) including the distance to the CP as a covariate in unconditional Resource Selection Functions (RSFs), as did in several studies, is quite inefficient to correct for the bias. Bias can be eliminated only by contrasting the actual use distribution to an appropriate neutral distribution that takes the CP forager behavior into account. (2) The need to specify such an appropriate neutral use distribution can be bypassed by relying on a conditional RSF, where the neutral use is assessed locally without reference to the CP.

ecology↗

bioRxiv2022

Spatial interactions between parrotfishes and implications for species coexistence

Home range behavior mediates species interactions and distributions, and spatiotemporal segregation may facilitate coexistence of competing species. We investigated home range behavior and spatial interactions in four common parrotfishes on coral reefs in Bonaire, Caribbean Netherlands, to determine how spatial interactions mediate species interactions and contribute to their coexistence. We first computed home ranges for males and females of each species. We then quantified spatial overlap (i.e., static interaction) between the home ranges of neighboring male parrotfishes and their activity in shared areas to estimate interaction potential for pairs of individuals. Finally, we analyzed dynamic interactions in simultaneously tracked, spatially co-occurring interspecific pairs of parrotfishes to investigate how they interact in shared space. Generally, spatial overlap of home ranges was much lower for intraspecific pairs than for interspecific pairs, but the probability of finding males in areas shared with males of other species was species-dependent. Males in interspecific pairs moved mostly independently of each other in shared areas, but we did find some evidence of avoidance in interspecific pairs sharing the most space. We discuss our findings within the context of parrotfish social and foraging ecology to further elucidate the spatial ecology of these functionally important reef fishes.

ecology↗

bioRxiv2020

Three-dimensional random walk models of individual animal movement and their application to trap counts modelling

BackgroundRandom walks (RWs) have proved to be a powerful modelling tool in ecology, particularly in the study of animal movement. An application of RW concerns trapping which is the predominant sampling method to date in insect ecology, invasive species, and agricultural pest management. A lot of research effort has been directed towards modelling ground-dwelling insects by simulating their movement in 2D, and computing pitfall trap counts, but comparatively very little for flying insects with 3D elevated traps. MethodsWe introduce the mathematics behind 3D RWs and present key metrics such as the mean squared displacement (MSD) and path sinuosity, which are already well known in 2D. We develop the mathematical theory behind the 3D correlated random walk (CRW) which involves short-term directional persistence and the 3D Biased random walk (BRW) which introduces a long-term directional bias in the movement so that there is an overall preferred movement direction. In this study, we consider three types of shape of 3D traps, which are commonly used in ecological field studies; a spheroidal trap, a cylindrical trap and a rectangular cuboidal trap. By simulating movement in 3D space, we investigated the effect of 3D trap shapes and sizes and of movement diffusion on trapping efficiency. ResultsWe found that there is a non-linear dependence of trap counts on the trap surface area or volume, but the effect of volume appeared to be a simple consequence of changes in area. Nevertheless, there is a slight but clear hierarchy of trap shapes in terms of capture efficiency, with the spheroidal trap retaining more counts than a cylinder, followed by the cuboidal type for a given area. We also showed that there is no effect of short-term persistence when diffusion is kept constant, but trap counts significantly decrease with increasing diffusion. ConclusionOur results provide a better understanding of the interplay between the movement pattern, trap geometry and impacts on trapping efficiency, which leads to improved trap count interpretations, and more broadly, has implications for spatial ecology and population dynamics.

ecology↗

bioRxiv2018

Identifying stationary phases in multivariate time-series for highlighting behavioural modes and home range settlements

O_LIRecent advances in bio-logging open promising perspectives in the study animal movements at numerous scales. It is now possible to record time-series of animal locations and ancillary data (e.g. activity level derived from on-board accelerometers) over extended areas and long durations with a high spatial and temporal resolution. Such time-series are often piecewise stationary, as the animal may alternate between different stationary phases (i.e. characterised by a specific mean and variance of some key parameter for limited periods). Identifying when these phases start and end is a critical first step to understand the dynamics of the underlying movement processes.\nC_LIO_LIWe introduce a new segmentation-clustering method we called segclust2d. It can segment bi-(or more generally multi-) variate time-series and possibly cluster the various segments obtained, corresponding to phases assumed to be stationary. It is easy to use, as it only requires specifying the minimum length of a segment (to prevent over-segmentation) based on biological considerations.\nC_LIO_LIAlthough this method can be applied to time-series of any nature, we focus here on two-dimensional piecewise time-series whose phases correspond at small scale to the expressions of different behavioural modes such as transit, feeding and resting, as characterised by two joint metrics such as speed and turning angles or, at larger scale, to temporary home ranges, characterised by stationary distributions of bivariate coordinates.\nC_LIO_LIUsing computer simulations, we show that segcust2d can rival and even outperform previous, more complex methods, which were specifically developed to highlight changes in movement modes or home range shifts (based on Hidden Markov or Ornstein-Uhlenbeck modelling, respectively), which, contrary to our method, require truly informative initial guesses to be efficient. Furthermore we demonstrate it on actual examples involving a zebras small scale movements and an elephants large scale movements, to illustrate the identification of various movement modes and of home range shifts, respectively.\nC_LI

ecology↗