Biology subjects

Peled, O.

Publications and source records attributed to Peled, O..

4 recordsLinked to original sources

bioRxiv2026

Contrasting effects of forest fragmentation on the genetics and microbiomes of an endangered arboreal primate

Landscape fragmentation, one of the leading drivers of biodiversity loss, can reshape both the genetics and microbiomes of wild populations. Although fragmentation is generally expected to limit gene flow and erode genetic diversity, and to disrupt host-associated microbial communities, these responses arise via different pathways and may therefore diverge within the same population. To understand how fragmentation simultaneously shapes population genetics and gut microbiomes, we analyzed fecal-derived host genomic and microbiome data from endangered, arboreal black howler monkeys (Alouatta pigra) across a fragmentation gradient. We then integrated these data with measures of ecological connectivity, habitat quality, and demography to identify the drivers of genetic and microbiome variation and structure. Multivariate analyses indicated that genetic patterns were shaped by both connectivity and habitat quality, whereas microbiome variation was driven mainly by habitat quality. Contrary to expectations under reduced realized connectivity with increasing isolation, monkeys showed the strongest gene flow signal in the most fragmented region, and higher genetic diversity and lower inbreeding than monkeys in continuous forest. Relatedness and isolation-by-distance patterns suggested that fragmentation has sex-specific effects on movement, disrupting the usual pattern of short-range male dispersal in the most fragmented region. Gut microbiomes, however, showed predicted negative responses to fragmentation: individuals in highly fragmented habitat had lower microbial diversity and compositional shifts consistent with lower-quality diets and increased exposure to disturbed environments. These results show contrasting biological responses to fragmentation within a single population, with genetic patterns likely resulting from compensatory behavioral flexibility and microbiome patterns reflecting local habitat degradation. Our findings underscore the need for conservation assessments that integrate multiple dimensions of population health rather than relying on any single indicator of fragmentation impact.

ecology↗

bioRxiv2025

Network-based genetic monitoring of landscape fragmentation

Habitat fragmentation is one of the most immediate and substantial threats to biodiversity, generating isolated populations with reduced genetic diversity. Genetic monitoring has become essential for detecting fragmentation and tracking its progress. However, the coherent interpretation of genetic monitoring data and understanding the genetic consequences of fragmentation require frameworks that accurately represent real-world complexity. Existing theoretical frameworks typically rely on simplified spatial structures and do not adequately capture the heterogeneous migration patterns of natural populations. Here, we integrate network theory and mathematical population genetics to develop a framework for studying the genetic consequences of fragmentation processes, explicitly accounting for heterogeneous connectivity and temporal dynamics. We apply this framework to examine how different fragmentation processes affect genetic measures commonly used in genetic monitoring. We find that different fragmentation scenarios produce substantially distinct trajectories in key genetic measures, sometimes exhibiting rapid transitional dynamics, suggesting that the interpretation of genetic monitoring data must be tailored to ecological contexts. Furthermore, fragmentation can cause deviations from classical theoretical expectations, such as the expected correlation between genetic and geographic distance (isolation-by-distance) or between genetic diversity and connectivity. Finally, we propose and demonstrate detectable early warning signals in genetic monitoring data that precede rapid transitional phases. Our framework thus provides a practical interpretation of genetic monitoring data, bridging the gap between idealized theoretical models and real-world connectivity dynamics.

genetics↗

bioRxiv2024

Data-driven analyses of social complexity in bees reveal phenotypic diversification following a major evolutionary transition

How social complexity evolved is a long-standing enigma. In most animal groups, social complexity is typically classified into a few discrete classes. This approach is oversimplified and constrains our inference of social evolution to a narrow trajectory consisting of transitions between classes. This approach also limits quantitative studies on the molecular and environmental drivers of social complexity. However, the recent accumulation of relevant quantitative data has now set the stage to overcome these limitations. Here, we propose a data-driven approach for studying the full diversity of social phenotypes. We curated and analyzed a comprehensive dataset encompassing 17 social traits for 77 species and studied the evolution of social complexity in bees. We found that corbiculate bees -- honey bees, stingless bees, and bumble bees -- underwent a major evolutionary transition [~]70 mya, which is inconsistent with the stepwise progression of the social ladder conceptual framework. This major evolutionary transition was followed by a phase of substantial phenotypic diversification of social complexity. Non-corbiculate bee lineages display a continuum of social complexity, ranging from solitary to simple societies, but do not reach levels of social complexity comparable to those of corbiculate bees. Bee evolution provides a unique demonstration of a macroevolutionary process in which a major transition removed biological constraints and opened novel evolutionary opportunities, driving the exploration of the landscape of social phenotypes. Our approach can be extended to incorporate additional data types and readily applied to illuminate the evolution of social complexity in additional animal groups.

evolutionary biology↗

bioRxiv2018

Human Subthalamic Nucleus Selectively Decreases its Response to the Go-Signal in a Motor Inhibition Context

To better understand the mechanism of movement facilitation and inhibition in the subthalamic nucleus (STN), we recorded subthalamic multiunit activity intra-operatively while parkinsonian patients (n=43 patients, 173 sites) performed increasingly complex oddball paradigms: auditory ( None-Go, n=7, 28), simple movement ( All-Go, n=7, 26) and movement inhibition ( Go-NoGo, n=29, 119) tasks. To enable physiological sampling of the different subthalamic nucleus domains in both hemispheres, each patient performed one of the oddball paradigms several times.\n\nThe human STN responded mainly to movement-involving tasks: movement execution at the motor STN and movement planning at the limbic-associative STN. In the limbic-associative STN, responses to the inhibitory cue (deviant tone) in the movement inhibition task were not significantly different from the simple movement task. However, responses to the go cue (frequent tone) were significantly reduced. The reduction was mainly in the negative component of the evoked response amplitude. Successful movement inhibition was correlated with higher baseline activity before the inhibitory cue.\n\nWe suggest that the STN adapts to movement inhibition context by selectively decreasing the amplitude of neuronal activity. Thus, the STN enables movement inhibition not by increasing responses to the inhibitory cue but by reducing responses to the release cue. The negative component of the evoked response probably facilitates movement and a higher baseline activity enables successful inhibition of movement. These discharge modulations were found in the ventromedial, non-motor domain of the STN and therefore suggest a significant role of the associative-limbic domains in movement planning and in global movement regulation.

neuroscience↗