Marc Ohlmann

Marc Ohlmann
Alpine Ecology Lab Université Grenoble Alpes

PhD Ecological modelling

About

21
Publications
6,276
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158
Citations
Citations since 2017
21 Research Items
158 Citations
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Introduction
I am currently Post-doc in Alpine Ecology Lab, Grenoble. My research is at the crossroads between ecology and mathematics. I particularly focus on statistical models of interactions, methods of network comparison on eDNA data and network visualisation. My website: https://marcohlmann.netlify.com/ You will find a tutorial on the 'econetwork' R package.

Publications

Publications (21)
Preprint
Full-text available
Trophic networks describe interactions between species at a given location and time. Due to environmental changes, anthropogenic perturbations or sampling effects, trophic networks may vary in space and time. The collection of network time series or networks in different sites thus constitutes a metanetwork. A crucial step toward the understanding...
Article
Full-text available
Urbanization may significantly alter the abundance, composition and phenology of natural communities of plants and pollinators. However, how such alterations eventually affect the structure of plant-pollinator interaction networks is still poorly known. Here, we investigate how the structure of plant-pollinator networks changes along an urbanizatio...
Preprint
Full-text available
We develop a spatially realistic model of mutualistic metacommunities that exploits the joint structure of spatial and interaction networks. This model exhibits a sharp transition between a stable non-null equilibrium state and a global extinction state. This behaviour allows defining a threshold on colonisation/extinction parameters for the long-t...
Article
Full-text available
Aim Although soil biodiversity is extremely rich and spatially variable, both in terms of species and trophic groups, we still know little about its main drivers. Here, we contrast four long‐standing hypotheses to explain the spatial variation of soil multi‐trophic diversity: energy, physiological tolerance, habitat heterogeneity and resource heter...
Article
Full-text available
The increasing severity and frequency of natural disturbances requires a better understanding of their effects on all compartments of biodiversity. In Northern Fennoscandia, recent large-scale moth outbreaks have led to an abrupt change in plant communities from birch forests dominated by dwarf shrubs to grass-dominated systems. However, the indire...
Preprint
Full-text available
Separating environmental effects from those of biotic interactions on species distributions has always been a central objective of ecology. Despite years of effort in analysing patterns of species co-occurrences and communities and the developments of sophisticated tools, we are still unable to address this major objective. A key reason is that the...
Preprint
Full-text available
The increasing severity and frequency of natural disturbances requires a better understanding of their effects on all compartments of biodiversity. In Northern Fennoscandia, recent large-scale moth outbreaks have led to an abrupt change in plant communities from birch forests dominated by dwarf shrubs to grass-dominated systems. However, the indire...
Thesis
Full-text available
Cette thèse s’intéresse aux liens entre réseaux d’interactions en écologie, espace et temps. On assiste à un changement croissant de représentation d’un communauté d’espèces, d’un ensemble d’espèces à un ensemble d’espèces et leurs interactions : un réseau d’interactions. On s’attachera alors à élaborer les prémisses d’une théorie spatiale des rése...
Article
Full-text available
Despite recent calls for integrating interaction networks into the study of large‐scale biodiversity patterns, we still lack a basic understanding of the functional characteristics of large interaction networks and how they are structured across environments. Here, building on recent advances in network science around the Eltonian niche concept, we...
Article
Full-text available
1.Much effort has been devoted to better understanding the effects of environment and biodiversity on ecosystem functioning. However, few studies have moved beyond measuring biodiversity as species richness of a single group and/or focusing on a single ecosystem function. While there is a growing recognition that along environmental gradients, the...
Article
Full-text available
Describing how ecological interactions change over space and time and how they are shaped by environmental conditions is crucial to understand and predict ecosystem trajectories. However, it requires having an appropriate framework to measure network diversity locally, regionally and between samples (a-, c-and b-diversity). Here, we propose a unify...
Article
Full-text available
Foundation plants shape the composition of local biotic communities and abiotic environments, but the impact of a plant's intraspecific variations on these processes is poorly understood. We examined these links in the alpine cushion moss campion (Silene acaulis) on two neighboring mountain ranges in the French Alps. Genotyping of cushion plants re...
Article
Full-text available
Investigating how trophic interactions influence the β-diversity of meta-communities is of paramount importance to understanding the processes shaping biodiversity distribution. Here, we apply a statistical method for inferring the strength of spatial dependencies between pairs of species groups. Using simulated community data generated from a mult...

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Projects

Projects (2)
Project
The project is devoted to the development of statistical methods specifically designed for analysing different types of ecological networks: trophic, mutualistic, competition or antagonistic and host- parasite systems. We propose to create a unique consortium of researchers combining applied statisticians with long-standing experience on life-science modeling and ecologists at the forefront of their domain to tackle the challenges posed by the advanced statistical modeling of ecological networks. Our proposal includes 1) integrating space and time dimensions in ecological networks modeling and developing tools for the comparison of networks along environmental gradients; 2) integrating multiple types of interactions, taking advantage of covariate information (such as species traits, distributions, phylogenies and environmental variables) when available; 3) incorporating sampling effects in our analyses and 4) providing predictions on ecosystem response to environmental changes.
Project
A major challenge for ecologists is to understand and predict the ecological consequences of climate change, land use change and disturbances. To meet this challenge, we need to account not only for environmental change effects on species performances and ranges but also for effects on species interactions. The alterations of species interactions are likely to create cascading effects that can result in non-linear responses, potentially leading to critical and irreversible transitions of ecosystems at short time scales but also over large spatial scales. The assumption that species interactions are only important at small spatial scales has indeed generated considerable debate. Until recently the prevailing idea was that biotic assembly processes (e.g. interspecific competition and trophic interactions) were only important at small spatial scales. Conceptual work and microcosms experiments early challenged this assumption, which has been strengthened by recent studies empirically demonstrating the importance of biotic interactions up to continental scales. It has been argued that determining the direction and magnitude of global change impacts on species interactions remains one of the greatest challenges for forecasting community and ecosystem dynamics. The main objective of the GlobNets project is thus to decipher multi-trophic assemblages at biogeographic scales and to understand their responses to spatial segregation, environmental gradients and/or human activities. To do so, GlobNets builds on new mathematical developments and environmental DNA metabarcoding. We will collect an unprecedented multi-trophic assemblage dataset of soil-plant biodiversity that covers the three super-kingdoms of life (Eukaryota, Bacteria and Archaea) across multiple forest plots along gradients of climate and land-use pressure in 12 distinct forest sites around the globe (tropical, temperate and boreal forests). GlobNets will address the following objectives: I. Develop publicly available multi-scale, multi-trophic and standardized data comprising sampled sites from major forest biomes of the world that contain information on species and functional group co-occurrences from the whole tree of life. In each sampled site, samples are replicated along environmental or disturbance gradients. II. Develop new mathematical and statistical tools for the analyses of multi-trophic community data from eDNA that allow for unbiased within, between and overall community diversity estimates (i.e. a, ß and ? components) and for an approximation of interaction probabilities within and across trophic levels. III. Based on I and II, map and describe the distribution of forest soil and plant diversity across biomes and test for which trophic levels the latitudinal diversity gradient hypothesis holds. IV. Analyse the response of forest soil and plant diversity to large-scale climate and regional-scale environmental and disturbance gradients, detect co-variation between trophic levels as well as between above and belowground compartments V.Based on a suitable sub-set of the dataset, provide a decomposition of diversity into a, ß, and ? components and test long-standing ecological hypotheses related to disturbance and stress gradients across climatic regions, specific abiotic drivers and trophic levels. VI.Based on the methods developed in II, conduct the first global biogeographical description of soil-based co-occurrence networks for a major ecosystem (i.e. forest) including members from the whole tree of life (i.e. Eukaryota, Bacteria and Archaea). VII.Based on a suitable subset of the data (i.e. including those interaction partners that are identified with enough certainty), investigate how strongly network complexity and modularity are influenced by large-scale climatic filters and regional-scale environmental and disturbance filters. Finally, provide a biogeographical description of network robustness based on simulations of cascading species extinctions.