Biology subjects

Haegeman, B.

Publications and source records attributed to Haegeman, B..

14 recordsLinked to original sources

bioRxiv2026

Connecting models, networks and experiments: Revisiting the role of viruses in marine carbon cycling

The marine microbial food web is a key driver of global carbon cycling, mediating the production, consumption and remineralisation of organic matter in the ocean. Within this food web, viruses exert strong top-down control by infecting and lysing both phytoplankton and heterotrophic bacteria. Although virus-induced mortality is recognised as a factor shaping microbial dynamics, accurately quantifying its contribution to carbon cycling remains difficult. A range of approaches have been used to estimate this contribution, notably: (1) dynamical microbial ecosystem models, (2) static carbon flux networks, and (3) direct measurements of virus-induced mortality, such as dilution assays. In this study, we bring these approaches together by formulating them within a common mathematical framework. This enables us to clarify the difference between two notions of lysis percentage in the literature, to compare predictions of previous microbial ecosystem models and flux network reconstructions, and to critically evaluate the theoretical approach of eliminating viruses from the system to explore their effects. Our analysis clarifies how the different approaches capture complementary aspects of the role of marine viruses in carbon cycling across varying spatial and temporal scales.

ecology↗

bioRxiv2025

An Alternative Approach to Compute the Likelihood for the DAISIE (Dynamic Assembly of Island biota through Speciation, Immigration, and Extinction) Model

Understanding island biodiversity requires studying the processes driving its assembly and examining how these processes vary over time, across lineages, and across different islands. The DAISIE (Dynamic Assembly of Island biota through Speciation, Immigration, and Extinction) framework has been developed for this purpose, and has advanced our understanding of island community assembly by estimating, from phylogenetic data, the contribution of the processes of colonization, speciation and extinction to island community assembly. However, the model assumes uniform colonization and diversification rates across lineages, ignoring potential variation in these rates caused by, for example, lineage-specific traits. This assumption thus restricts the models capacity to capture complex colonization and diversification dynamics, and may consequently bias inference of colonization and diversification dynamics on islands. An extension of the framework behind these more complex dynamics is therefore desired. However, for this state-dependent colonization and diversification extension, the current computation of the likelihood of the model given phylogenetic data is computationally prohibitive. In this study, we therefore propose an alternative approach to computing the DAISIE likelihood, under the assumption of diversity-independent colonization and diversification. Our novel approach is based on the pruning algorithm (which calculates the likelihoods of comparative data given a tree and a model) that has been used for computing the likelihood of SSE (State-dependent Speciation and Extinction) models, which traces lineage history backward in time from the present day to the root of the tree. We demonstrate that our alternative approach reproduces DAISIEs predictions under diversity-independent colonization and diversification. This is important because no independent evaluation of the likelihood computation in DAISIE has been available. Our alternative approach not only confirms DAISIE results for diversity-independent colonization and diversification, it also gives more confidence in the results under diversity-dependence. Furthermore, our alternative approach offers greater computational efficiency. Finally, it provides a flexible framework for incorporating state-dependent dynamics in colonization, speciation, and extinction processes.

evolutionary biology↗

bioRxiv2023

The effects of warming on the stability of consumer-resource interactions

Temperature regulates the physiology and behaviour of organisms. Thus, changing temperatures induce dynamics in species interactions. Considering that consumer-resource interactions underpin ecological communities, the impacts of warming on the stability of consumer-resource interactions have been extensively studied. However, a consensus among empirically determined warming-stability relationships and a clear understanding thereof is lacking. To investigate these systematically, we propose a simplified theoretical framework that can incorporate empirical data in three steps. First, we constrain stability to intrinsic oscillations to avoid comparing disparate stability notions. Second, we reduce complexity by utilising a one-dimensional stability metric. Third, we enable the direct comparison of all data by converting all thermal dependence parameterisations into a single function, with two parameters in the exponent determining its shape. The empirical data generate four different warming-stability relationships: stability increases, decreases, is hump-shaped or U-shaped with temperature. The diversity of warming-stability relationships, though partly attributable to context-dependence, is fundamentally caused by sensitivity to two factors: how the processes within the functional response are defined and the thermal dependence of carrying capacity. Consistency across studies regarding the former and acquiring more data on the latter should help uncover systematic patterns in the thermal dependence of stability in consumer-resource interactions.

ecology↗

bioRxiv2023

Epigenetic variation causes heritable variation in complex traits in the mollusk Biomphalaria glabrata, vector of the human parasite Schistosoma mansoni

DNA methylation variation may play a role in phenotypic variation as it can be directly affected by the environment and be inherited. DNA methylation variations were introduced into the parasite vector snail Biomphalaria glabrata with low genetic diversity by chemical treatment in F0 and followed over 3 generations using epigenetic recombinant inbred lines (epiRILs). We observed phenotypic variation in complex traits such as fecundity and susceptibility to infestation by Schistosoma mansoni and DNA methylation differences in F3. Both, increase and decrease of infestation success (up to 100% and down to 20% prevalence in epiRILs and from 86% to 94% in control RILs) indicated variation in complex resistance/compatibility trait. Average prevalence in control RILs was 84{+/-}5% but only 68{+/-}21 % in epiRILs. Fecundity also changed and was in average 47{+/-}7% in control RILs and 59{+/-}18% in epiRILs, being 12% higher in epiRILs. We found that the heritability h2 of the fecundity in the epiRILs was between 0.5 and 0.6 depending on the method used to estimate it. We developed a model for introducing epimutant offspring snails into resident susceptible populations. If genetic assimilation of the resistant phenotype occured in a small fraction of the introduced epimutant snails, we predict that the susceptible phenotype is replaced by the resistant phenotype after 50-70 generations.

ecology↗

bioRxiv2022

The limits to ecological limits to diversification

AO_SCPLOWBSTRACTC_SCPLOWWhile the theory of micro-evolution by natural selection assigns a crucial role to competition, its role in macroevolution is less clear. Phylogenetic evidence for a decelerating accumulation of lineages suggests a feedback of lineage diversity on diversification, i.e., ecological limits to diversification. However, does this feedback only occur between close relatives, or do distant relatives also influence their diversification? In other words: are there phylogenetic limits to these ecological limits? Islands form ideal systems to answer these questions, because their boundedness facilitates an overview of all potential competitors. The DAISIE (Dynamic Assembly of Island biota through Speciation Immigration and Extinction) framework allows for testing the presence of diversity-dependence on islands given phylogenetic data on colonization and branching times. The current inference models in DAISIE assume that this diversity-dependence only applies within a colonizing clade, which we term clade-specific (CS) diversity-dependence. Here we introduce a new DAISIE model that assumes that diversity-dependence applies to all species regardless of their ancestry, i.e. diversity-dependence applies both to species within the same clade and between different clades. We call this island-wide (IW) diversity-dependence. Here we present a method to compute a likelihood for this model and develop a statistical procedure based on likelihood ratio bootstrapping to compare it to the likelihood of the CS model in order to overcome biases known for standard model selection. We apply it to the diversification of Eleutherodactylus frogs on Hispaniola. Across the Greater Antilles archipelago, this radiation shows repeated patterns of diversification in ecotypes which are similar across clades. This could be suggestive of overlapping niche space and hence between-clade interactions, i.e. IW diversity-dependence. But it could also be suggestive of only within-clade interactions, because between-clade interactions would have blocked the same ecotype re-appearing. We find that the CS model fits the data much better than the IW model, indicating that different colonizations, while resulting in similar ecotypes, are sufficiently distinct to avoid interacting strongly. We argue that non-overlapping distributions between clades (both spatially and in terms of ecotypes) cannot be used as evidence of CS diversity-dependence, because this pattern may be a consequence of IW diversity-dependence. By contrast, by using phylogenetic data rather than distributional data our method does allow for inferring the phylogenetic limits to ecological limits to diversification. We discuss how our new IW model advances our understanding also in other ways, ranging from identifying priority effects to modelling the spread of an epidemic in island-like systems, such as schools or hospitals.

evolutionary biology↗

bioRxiv2020

A framework to improve predictions of warming effects on consumer-resource interactions

Changes in temperature affect consumer-resource interactions, which underpin the functioning of ecosystems. However, existing studies report contrasting predictions regarding the impacts of warming on biological rates and community dynamics. To improve prediction accuracy and comparability, we develop an approach that combines sensitivity analysis and aggregate parameters. The former determines which biological parameters impact the community most strongly. The use of aggregate parameters (i.e., maximal energetic efficiency,{rho} , and interaction strength,{kappa} ), that combine multiple biological parameters, increases explanatory power and reduces the complexity of theoretical analyses. We illustrate the approach using empirically-derived thermal dependence curves of biological rates and applying it to consumer-resource biomass ratio and community stability. Based on our analyses, we generate four predictions: 1) resource growth rate regulates biomass distributions at mild temperatures, 2) interaction strength alone determines the thermal boundaries of the community, 3) warming destabilises dynamics at low and mild temperatures only, 4) interactions strength must decrease faster than maximal energetic efficiency for warming to stabilise dynamics. We argue for the potential benefits of directly working with the aggregate parameters to increase the accuracy of predictions on warming impacts on food webs and promote cross-system comparisons.

ecology↗

bioRxiv2020

Habitat fragmentation and food security in crop pollination systems

Ensuring stable food supplies is recognized as a major challenge for the 21st century, and one of the UN Sustainable Development Goals. Biodiversity-based approaches to food security are increasingly being supported based on the fact that biodiversity can increase and stabilize crop yields. But agricultural systems are often highly fragmented and it is unclear how such fragmentation affects biodiversity and food production, limiting our capacity to manage agricultural landscapes for food security. Here, we develop a model of crop yield dynamics to investigate how fragmentation of natural habitats for agricultural conversion impacts food production, with a focus on crop pollination. Our results show that fragmentation produces spatial and biodiversity-mediated effects that affect the mean and stability of pollination-dependent crops, with strong consequences for food security. The net effects of fragmentation depend on the strength of the spillover of pollinators to crop land and the degree to which crops depend on animal pollination. Our study sheds new light in the food security debate by showing that high and stable yields depend on biodiversity and the spatial structure of agricultural landscapes, and by revealing the ecological mechanisms of food security in crop pollination systems.

ecology↗

bioRxiv2019

Additional analytical support for a new method to compute the likelihood of diversification models

Molecular phylogenies have been increasingly recognized as an important source of information on species diversification. For many models of macro-evolution, analytical likelihood formulas have been derived to infer macro-evolutionary parameters from phylogenies. A few years ago, a general framework to numerically compute such likelihood formulas was proposed, which accommodates models that allow speciation and/or extinction rates to depend on diversity. This framework calculates the likelihood as the probability of the diversification process being consistent with the phylogeny from the root to the tips. However, while some readers found the framework presented in Etienne et al. (2012) convincing, others still questioned it (personal communication), despite numerical evidence that for special cases the framework yields the same (i.e. within double precision) numerical value for the likelihood as analytical formulas do that were independently derived for these special cases. Here we prove analytically that the likelihoods calculated in the new framework are correct for all special cases with known analytical likelihood formula. Our results thus add substantial mathematical support for the overall coherence of the general framework.

evolutionary biology↗

bioRxiv2019

Stoichiometric constraints modulate the effects of temperature and nutrients on biomass distribution and community stability

AO_SCPLOWBSTRACTC_SCPLOWTemperature and nutrients are two of the most important drivers of global change. Both can modify the elemental composition (i.e. stoichiometry) of primary producers and consumers. Yet their combined effect on the stoichiometry, dynamics, and stability of ecological communities remains largely unexplored. To fill this gap, we extended the Rosenzweig-MacArthur consumer-resource model by including thermal dependencies, nutrient dynamics, and stoichiometric constraints on both the primary producer and the consumer. We found that stoichiometric constraints dampen the paradox of enrichment and increased persistence at high nutrient levels. Nevertheless, they also reduced consumer persistence at extreme temperatures. Finally, we also found that stoichiometric constraints can strongly influence biomass distribution across trophic levels by modulating consumer assimilation efficiency and resource growth rates along the environmental gradients. In the Rosenzweig-MacArthur model, consumer biomass exceeded resource biomass for most parameter values whereas, in the stoichiometric model, consumer biomass was strongly reduced and sometimes lower than resource biomass. Our findings highlight the importance of accounting for stoichiometric constraints as they can mediate the temperature and nutrient impact on the dynamics and functioning of ecological communities.

ecology↗

bioRxiv2018

The variability spectrum of ecological communities: How common and rare species shape stability patterns

Empirical knowledge of ecosystem stability and diversity-stability relationships is mostly based on the analysis of temporal variability of population and ecosystem properties. Variability, however, often depends on external factors that act as disturbances, making it difficult to compare its value across systems and relate it to other stability concepts. Here we show how variability, when viewed as a response to stochastic perturbations, can reveal inherent stability properties of ecological communities, with clear connections with other stability notions. This requires abandoning one-dimensional representations, in which a single variability measurement is taken as a proxy for how stable a system is, and instead consider the whole set of variability values associated to a given community, reflecting the whole set of perturbations that can generate variability. Against the vertiginous dimensionality of the perturbation set, we show that a generic variability-abundance pattern emerges from community assembly, which relates variability to the abundance of perturbed species. As a consequence, the response to stochastic immigration is governed by rare species while common species drive the response to environmental perturbations. In particular, the contrasting contributions of different species abundance classes can lead to opposite diversity-stability patterns, which can be understood from basic statistics of the abundance distribution. Our work shows that a multidimensional perspective on variability allows one to better appreciate the dynamical richness of ecological systems and the underlying meaning of their stability patterns.

ecology↗

bioRxiv2018

Trade-offs in provisioning and stability of multiple ecosystem services in agroecosystems

Changes in land use generate trade-offs in the delivery of ecosystem services in agricultural landscapes. However, we know little about how the stability of ecosystem services responds to landscape composition, and what ecological mechanisms underlie these trade-offs. Here, we develop a model to investigate the dynamics of three ecosystem services in intensively-managed agroecosystems, i.e. pollination-independent crop yield, crop pollination, and biodiversity. Our model reveals trade-offs and synergies imposed by landscape composition that affect not only the magnitude but also the stability of ecosystem service delivery. Trade-offs involving crop pollination are strongly affected by the degree to which crops depend on pollination and by their relative requirement for pollinator densities. We show conditions for crop production to increase with biodiversity and decreasing crop area, reconciling farmers profitability and biodiversity conservation. Our results further suggest that, for pollination-dependent crops, management strategies that focus on maximising yield will often overlook its stability. Given that agriculture has become more pollination-dependent over time, it is essential to understand the mechanisms driving these trade-offs to ensure food security.

ecology↗

bioRxiv2017

The relationship between the spatial scaling of biodiversity and ecosystem stability

Ecosystem stability and its link with biodiversity have been mainly studied at the local scale. Here we present a simple theoretical model to address the joint dependence of diversity and stability on spatial scale, from local to continental. The notion of stability we use is based on the temporal variability of an ecosystem-level property, such as primary productivity. In this way, our model integrates the well-known species-area relationship (SAR) with a recent proposal to quantify the spatial scaling of stability, called the invariability-area relationship (IAR). To explore the possible links between the two relationships, we contrast two assumptions about the spatial decay of correlations. In case species differences determine spatial decorrelation, the IAR is a duplicate of the SAR; in case decorrelation is directly determined by spatial separation, the IAR is unrelated to the SAR. We apply the two model variants to explore the effects of species loss and habitat destruction on stability, and find a rich variety of multi-scale spatial dependencies. Our work emphasizes the importance of studying diversity and stability across spatial scales, and provides a point of reference for mechanistic models and data analyses.

ecology↗

bioRxiv2017

How ecosystems recover from pulse perturbations: A theory of short- to long-term responses

Quantifying stability properties of ecosystems is an important problem in ecology. A common approach is based on the recovery from pulse perturbations, and posits that the faster ecosystems return to their pre-perturbation state, the more stable they are. In theoretical studies the recovery dynamics are often collapsed into a single quantity: the long-term rate of return, called asymptotic resilience. However, empirical studies typically measure the recovery dynamics at much shorter time scales. In this paper we explain why asymptotic resilience is rarely representative of the short-term recovery. First, we show that, in contrast to asymptotic resilience, short-term return rates depend on features of the perturbation, in particular on the way its intensity is distributed over species. We argue that empirically relevant predictions can be obtained by considering the median response over a set of perturbations, for which we provide explicit formulas. Next, we show that the recovery dynamics are controlled through time by different species: abundant species tend to govern the short-term recovery, while rare species often dominate the long-term recovery. This shift from abundant to rare species typically causes short-term return rates to be unrelated to asymptotic resilience. Finally, we discuss how these findings might help to better connect empirical observations and theoretical predictions.

ecology↗

bioRxiv2016

Resilience, invariability, and ecological stability across levels of organization

Ecological stability is a bewildering broad concept. The most common stability measures are asymptotic resilience, widely used in theoretical studies, and measures based on temporal variability, commonly used in empirical studies. We construct measures of invariability, defined as the inverse of variability, that can be directly compared with asymptotic resilience. We show that asymptotic resilience behaves like the invariability of the most variable species, which is often a rare species close to its extinction boundary. Therefore, asymptotic resilience displays complete loss of stability with changes in community composition. In contrast, mean population invariability and ecosystem invariability are insensitive to rare species and quantify stability consistently whether details of species composition are considered or not. Invariability provides a consistent framework to predict diversity-stability relationships that agree with empirical data at population and ecosystem levels. Our findings can enhance the dialogue between theoretical and empirical stability studies.

ecology↗