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Institute
The AlpArray seismic network
(2018)
The AlpArray programme is a multinational, European consortium to advance our understanding of orogenesis and its relationship to mantle dynamics, plate reorganizations, surface processes and seismic hazard in the Alps-Apennines-Carpathians-Dinarides orogenic system. The AlpArray Seismic Network has been deployed with contributions from 36 institutions from 11 countries to map physical properties of the lithosphere and asthenosphere in 3D and thus to obtain new, high-resolution geophysical images of structures from the surface down to the base of the mantle transition zone. With over 600 broadband stations operated for 2 years, this seismic experiment is one of the largest simultaneously operated seismological networks in the academic domain, employing hexagonal coverage with station spacing at less than 52 km. This dense and regularly spaced experiment is made possible by the coordinated coeval deployment of temporary stations from numerous national pools, including ocean-bottom seismometers, which were funded by different national agencies. They combine with permanent networks, which also required the cooperation of many different operators. Together these stations ultimately fill coverage gaps. Following a short overview of previous large-scale seismological experiments in the Alpine region, we here present the goals, construction, deployment, characteristics and data management of the AlpArray Seismic Network, which will provide data that is expected to be unprecedented in quality to image the complex Alpine mountains at depth.
Using individual-based modeling to understand grassland diversity and resilience in the Anthropocene
(2020)
The world’s grassland systems are increasingly threatened by anthropogenic change. Susceptible to a variety of different stressors, from land-use intensification to climate change, understanding the mechanisms driving the maintenance of these systems’ biodiversity and stability, and how these mechanisms may shift under human-mediated disturbance, is thus critical for successfully navigating the next century. Within this dissertation, I use an individual-based and spatially-explicit model of grassland community assembly (IBC-grass) to examine several processes, thought key to understanding their biodiversity and stability and how it changes under stress. In the first chapter of my thesis, I examine the conditions under which intraspecific trait variation influences the diversity of simulated grassland communities. In the second and third chapters of my thesis, I shift focus towards understanding how belowground herbivores influence the stability of these grassland systems to either a disturbance that results in increased, stochastic, plant mortality, or eutrophication.
Intraspecific trait variation (ITV), or variation in trait values between individuals of the same species, is fundamental to the structure of ecological communities. However, because it has historically been difficult to incorporate into theoretical and statistical models, it has remained largely overlooked in community-level analyses. This reality is quickly shifting, however, as a consensus of research suggests that it may compose a sizeable proportion of the total variation within an ecological community and that it may play a critical role in determining if species coexist. Despite this increasing awareness that ITV matters, there is little consensus of the magnitude and direction of its influence. Therefore, to better understand how ITV changes the assembly of grassland communities, in the first chapter of my thesis, I incorporate it into an established, individual-based grassland community model, simulating both pairwise invasion experiments as well as the assembly of communities with varying initial diversities. By varying the amount of ITV in these species’ functional traits, I examine the magnitude and direction of ITV’s influence on pairwise invasibility and community coexistence. During pairwise invasion, ITV enables the weakest species to more frequently invade the competitively superior species, however, this influence does not generally scale to the community level. Indeed, unless the community has low alpha- and beta- diversity, there will be little effect of ITV in bolstering diversity. In these situations, since the trait axis is sparsely filled, the competitively inferior may suffer less competition and therefore ITV may buffer the persistence and abundance of these species for some time.
In the second and third chapters of my thesis, I model how one of the most ubiquitous trophic interactions within grasslands, herbivory belowground, influences their diversity and stability. Until recently, the fundamental difficulty in studying a process within the soil has left belowground herbivory “out of sight, out of mind.” This dilemma presents an opportunity for simulation models to explore how this understudied process may alter community dynamics. In the second chapter of my thesis, I implement belowground herbivory – represented by the weekly removal of plant biomass – into IBC-grass. Then, by introducing a pulse disturbance, modelled as the stochastic mortality of some percentage of the plant community, I observe how the presence of belowground herbivores influences the resistance and recovery of Shannon diversity in these communities. I find that high resource, low diversity, communities are significantly more destabilized by the presence of belowground herbivores after disturbance. Depending on the timing of the disturbance and whether the grassland’s seed bank persists for more than one season, the impact of the disturbance – and subsequently the influence of the herbivores – can be greatly reduced. However, because human-mediated eutrophication increases the amount of resources in the soil, thus pressuring grassland systems, our results suggest that the influence of these herbivores may become more important over time.
In the third chapter of my thesis, I delve further into understanding the mechanistic underpinnings of belowground herbivores on the diversity of grasslands by replicating an empirical mesocosm experiment that crosses the presence of herbivores above- and below-ground with eutrophication. I show that while aboveground herbivory, as predicted by theory and frequently observed in experiments, mitigates the impact of eutrophication on species diversity, belowground herbivores counterintuitively reduce biodiversity. Indeed, this influence positively interacts with the eutrophication process, amplifying its negative impact on diversity. I discovered the mechanism underlying this surprising pattern to be that, as the herbivores consume roots, they increase the proportion of root resources to root biomass. Because root competition is often symmetric, herbivory fails to mitigate any asymmetries in the plants’ competitive dynamics. However, since the remaining roots have more abundant access to resources, the plants’ competition shifts aboveground, towards asymmetric competition for light. This leads the community towards a low-diversity state, composed of mostly high-performance, large plant species. We further argue that this pattern will emerge unless the plants’ root competition is asymmetric, in which case, like its counterpart aboveground, belowground herbivory may buffer diversity by reducing this asymmetry between the competitively superior and inferior plants.
I conclude my dissertation by discussing the implications of my research on the state of the art in intraspecific trait variation and belowground herbivory, with emphasis on the necessity of more diverse theory development in the study of these fundamental interactions. My results suggest that the influence of these processes on the biodiversity and stability of grassland systems is underappreciated and multidimensional, and must be thoroughly explored if researchers wish to predict how the world’s grasslands will respond to anthropogenic change. Further, should researchers myopically focus on understanding central ecological interactions through only mathematically tractable analyses, they may miss entire suites of potential coexistence mechanisms that can increase the coviability of species, potentially leading to coexistence over ecologically-significant timespans. Individual-based modelling, therefore, with its focus on individual interactions, will prove a critical tool in the coming decades for understanding how local interactions scale to larger contexts, and how these interactions shape ecological communities and further predicting how these systems will change under human-mediated stress.
Ecosystems respond in various ways to disturbances. Quantifying ecological stability therefore requires inspecting multiple stability properties, such as resistance, recovery, persistence and invariability. Correlations among these properties can reduce the dimensionality of stability, simplifying the study of environmental effects on ecosystems. A key question is how the kind of disturbance affects these correlations. We here investigated the effect of three disturbance types (random, species-specific, local) applied at four intensity levels, on the dimensionality of stability at the population and community level. We used previously parameterized models that represent five natural communities, varying in species richness and the number of trophic levels. We found that disturbance type but not intensity affected the dimensionality of stability and only at the population level. The dimensionality of stability also varied greatly among species and communities. Therefore, studying stability cannot be simplified to using a single metric and multi-dimensional assessments are still to be recommended.
Intraspecific trait variation (ITV) is thought to play a significant role in community assembly, but the magnitude and direction of its influence are not well understood. Although it may be critical to better explain population persistence, species interactions, and therefore biodiversity patterns, manipulating ITV in experiments is challenging. We therefore incorporated ITV into a trait‐ and individual‐based model of grassland community assembly by adding variation to the plants’ functional traits, which then drive life‐history tradeoffs. Varying the amount of ITV in the simulation, we examine its influence on pairwise‐coexistence and then on the species diversity in communities of different initial sizes. We find that ITV increases the ability of the weakest species to invade most, but that this effect does not scale to the community level, where the primary effect of ITV is to increase the persistence and abundance of the competitively‐average species. Diversity of the initial community is also of critical importance in determining ITV's efficacy; above a threshold of interspecific diversity, ITV does not increase diversity further. For communities below this threshold, ITV mainly helps to increase diversity in those communities that would otherwise be low‐diversity. These findings suggest that ITV actively maintains diversity by helping the species on the margins of persistence, but mostly in habitats of relatively low alpha and beta diversity.
Genomic and epigenomic determinants of heat stress-induced transcriptional memory in Arabidopsis
(2023)
Background
Transcriptional regulation is a key aspect of environmental stress responses. Heat stress induces transcriptional memory, i.e., sustained induction or enhanced re-induction of transcription, that allows plants to respond more efficiently to a recurrent HS. In light of more frequent temperature extremes due to climate change, improving heat tolerance in crop plants is an important breeding goal. However, not all heat stress-inducible genes show transcriptional memory, and it is unclear what distinguishes memory from non-memory genes. To address this issue and understand the genome and epigenome architecture of transcriptional memory after heat stress, we identify the global target genes of two key memory heat shock transcription factors, HSFA2 and HSFA3, using time course ChIP-seq.
Results
HSFA2 and HSFA3 show near identical binding patterns. In vitro and in vivo binding strength is highly correlated, indicating the importance of DNA sequence elements. In particular, genes with transcriptional memory are strongly enriched for a tripartite heat shock element, and are hallmarked by several features: low expression levels in the absence of heat stress, accessible chromatin environment, and heat stress-induced enrichment of H3K4 trimethylation. These results are confirmed by an orthogonal transcriptomic data set using both de novo clustering and an established definition of memory genes.
Conclusions
Our findings provide an integrated view of HSF-dependent transcriptional memory and shed light on its sequence and chromatin determinants, enabling the prediction and engineering of genes with transcriptional memory behavior.