Biology subjects

Liechti, J. I.

Publications and source records attributed to Liechti, J. I..

3 recordsLinked to original sources

bioRxiv2025

Positive effects of landscape diversity on vegetation productivity at the kilometer scale

AO_SCPLOWBSTRACTC_SCPLOWBroad evidence suggests a positive relationship between local species richness and ecosystem functioning 1,2. However, Earths terrestrial surface is formed by a mosaic of different habitats, which constitutes a higher level of diversity known as landscape diversity. Recent studies indicate that landscape diversity can also promote ecosystem functions, including primary productivity, but the underlying mechanisms and relevant spatial scales remain poorly understood 3,4. Here, we combine satellite remote sensing of vegetation productivity with high-resolution land cover data to investigate the effects of landscape diversity on ecosystem functioning across different spatial scales. Using a plot network covering North America, we find that the observed landscape-wide effects cannot be explained by local-scale interactions along ecosystem interfaces. In a subsequent, global-scale analysis, we instead demonstrate that landscape diversity effects are most strongly associated to landscape diversity at a spatial scale of a few kilometers. This association holds across continents and climatic zones, indicating that this pattern is universal. Our investigation therefore suggests that effective land management and biodiversity conservation strategies must integrate both local species richness and higher-level organizational diversity, such as landscape diversity, to ensure robust ecosystem functioning.

ecology↗

bioRxiv2020

Quantifying the influence of space on social group structure

When studying social behaviour, it can be important to determine whether the behaviour being recorded is actually driven by the social preferences of individuals. Many studies of animal social networks therefore attempt to disentangle social preferences from spatial preferences or restrictions. As such, there are a large number of techniques with which to test whether results from network analysis can be explained by random interactions, or interactions driven by similarities in space use. Selecting which of these methods to use will require determining to what extent space might influence social structure. Here we present a simple method (Social Spatial Community Assignment Test) to quantify the similarity between social and spatial group structure. We then apply this method to both simulated and empirical data of social interactions to demonstrate that it can successfully tease apart social and spatial explanations for groups. We first show that it can resolve the relative importance of space and social preferences in three simulated datasets in which interaction patterns are driven purely by space use, purely by social preferences or a mixture of the two. We then apply it to empirical data from a long-term study of free-ranging house mice. We find that while social structure is similar to spatial structure, there is still evidence for individuals possessing social preferences, with the importance of these preferences fluctuating between seasons. Our method provides a robust way of assessing the overlap between spatial and social structure, which will be invaluable to researchers when investigating the underlying drivers of social structure in wild populations.

animal behavior and cognition↗

bioRxiv2020

Contact patterns reveal a stable dynamic community structure with fission-fusion dynamics in wild house mice

Living in groups is a widely adopted strategy in gregarious species. For group-living individuals it is crucial to be capable to integrate into a social structure. While there is an intuitive understanding that the concept of a group arises through some form of cohesion between its members, the exact definition of what constitutes a group and thus tasks like the detection of the dynamics of a group over time is a challenge. One way of measuring cohesion is through direct interactions between individuals. However, there is increasing evidence that associations between individuals can be mediated by others, and thus, that the drivers for group cohesion extend beyond direct individual interactions. We use dynamic community detection, allowing to relate individuals beyond direct contacts, both structurally and temporally, to study the social structure in a long-term study of a population of free-ranging house mice in a barn in Switzerland. During the 2-year study period, mice had unlimited access to food, and population density increased by 50%. Despite strong fluctuations in individual contact behaviour, population demography and structure embed into long-lived dynamic communities that are characterised by spatial fidelity, persist over several seasons and reproduction cycles, and considerably extend the life-span of single individuals. Within these multi-male and multi-female communities, seasonal changes strongly affect their structure, leading to fission-fusion like dynamics. We identify female-female interactions as the main driver for the longevity of these communities, a finding that contrasts with prior reports of the importance of a dominant male for the stability of a group. Moreover, males have a drastically shorter presence time in the study population and more often move between communities than females. Nevertheless, interacting with other breeding males in stable communities increases the duration of male presence and thus, potentially, reproductive success. Our analysis of contact patterns in a rodent that uses shelters to rest, hide and rear offspring emphasises the importance of female-bonded communities in the structuring of the population.

ecology↗