The present proposal aims to study the processes linked to living in groups (that we call sociality) in an ecological framework, coupling data (from both the lab and the field) to theory. Our strategy to tackle this overall goal is through a synthetic and interdisciplinary approach between biology and physics, which combines theory and data to enhance reliability and conceptual advances while testing ecological hypotheses. The frames of movement ecology and searching behaviour connect the two sub-projects, and we incorporate the interactions between individuals and the resulting social processes to explore their consequences for population dynamics in social animals. We will develop theory to make explicit testable predictions for specific social systems for which we have a deep previous ecological knowledge. Importantly, we will also be sharing experimental infrastructures and computational facilities between the two institutions. This challenging line of work requires a coordinated project with two complementary, interdisciplinary approaches merging concepts, infrastructures, tools and theories that have been addressed by the disciplines of ecology and physics. The history of collaboration between the two research groups and their promising outputs corroborate the fruitful potential of this type of approaches that have the vocation of trespassing closed and rigid scientific disciplines. We anticipate that having a coordinated project with those two disciplines would provide an innovative perspective of sociality and will allow for a major breakthrough at the frontier of scientific research.

PIs: Frederic Bartumeus and Daniel Oro

PhD Student: Pol Fernandez

Partners: Daniel Campos and Vicenç Mendez (UAB, Dept. of Physics)

 

 

Under the current global change scenario, it is essential to understand how individuals and populations are affected and how they respond to perturbations. Additionally, improving quantitative criteria to assess the conservation status of species and populations are needed to optimize the prioritization when using public resources and maximize our ability to anticipate and predict biodiversity loss. Resilience is the ability of a system to buffer external disturbances and not collapse. Several factors may affect the ability to respond and counterbalance a perturbation, and that capacity determines the resilience of populations. Resilience will likely depend on both the life history of the species, and the type and magnitude of perturbations. Another issue that is usually missed when assessing the effect of perturbations on populations is individual heterogeneity, since all individuals in a population are usually considered identical. Moreover, much of ecological theory and analytical tools for Conservation Biology are based on the idea that the observed states and dynamics of ecological systems can be represented by stable asymptotic behavior of models describing such systems. In contrast to the implied long time scales of asymptotic behavior in mathematical models, both observations of ecological systems and questions related to the management of populations under perturbations are typically focused on relatively short time scales, when transient phenomena occur. To understand and consider these transient dynamics is crucial if we aim to improve our precision and predictability in conservation biology. We will use demography as a natural scientific framework to develop a new integrative conceptual and analytical framework to understand transient dynamics and quantify resilience in natural populations. With this project, we specifically aim: a) to determine the role of individual heterogeneity in population dynamics, b) to analyze and understand transient dynamics under different types of environmental perturbations, c) to quantify resilience and improve current conservation criteria for the management of biodiversity. To accomplish these objectives, we will combine theory and empiric analyses to analyze the transient and asymptotic dynamics and the resilience of populations subjected to perturbations. The project will take advantage of the long term demographic monitoring of two seabird species (more than 4 decades of individual data and more than 50000 individuals marked). These species are two excellent case studies since: (i) they have experienced different types of anthropic perturbations, with some local populations gone extinct; (ii) they show strong individual heterogeneities in fitness traits, some due to personality traits. Additionally, we will simulate transient dynamics and quantify resilience in other species and populations with different life histories and individual heterogeneities, and affected by other types of perturbations. To help developing this
new Conservation Demography framework and to provide unified conservation criteria for all EU State members, we have reunited an outstanding Working Team and we aim to launch the International Network of Conservation Demography Research Expertise. The
development of this new integrative conceptual and analytical framework should allow us to improve the reliability of our conservation diagnosis and our predictive capacity in Population Ecology and Conservation Biology.

Life started in the oceans. Oceans cover the majority of Earth’s surface and are the single largest ecosystem on the planet. Billions of humans live in coastal areas and depend on the functioning of this ecosystem to live. Unfortunately, human activities are seriously
endangering the health of the marine ecosystem. It is therefore critical to raise awareness of the richness of this ecosystem, its importance, the challenges it faces and what we, as citizens of the world, can do to improve and preserve it through our personal choices. With the MCSA Researchers Night proposal Ocean Night we aim to contribute to this challenge by raising marine science literacy across the general population and promoting the appreciation of the importance of the marine ecosystem. Our proposal brings together all public Research Institutes across Spain working on marine science for a comprehensive 2-years outreach program.
We will leverage the substantial outreach experience of the Institutes to deliver a diverse and coherent program of events aimed at engaging a geographically wide and socially diverse set of regions within Spain.

Global change is the phenomenon related to anthropogenic impacts on the biosphere and its biodiversity. An impact that particularly affects industrialized countries is the abandonment of rural areas, with significant consequences in the transformation of the habitat and the dynamics of ecosystems. The mountainous regions suffer in particular from this abandonment, which generates the advance of forests and maquis with the consequent decline of the ecological communities of open spaces. In those regions, one of the traditional activities that are still maintained is extensive livestock farming, but little is known about its ecosystem services and its effects on the spatiotemporal dynamics of the ecological communities associated with pastures. Although livestock plays the role that wild ungulates once played in food webs, there is no scientific evidence about the optimal level of grazing that improves the management of biodiversity in mountain ecosystems and at the same time ensures the sustainability of the livestock sector.

The project will use a socio-ecological conceptual framework, which will holistically assess the influence that livestock management dynamics have on herbaceous plant and butterfly communities, which are excellent bioindicators of the conservation state of mountain ecosystems. The study will be carried out in the Pyrenees at different spatial-temporal scales, using both field data that we have collected in recent decades and those generated in the project. On a local scale, we will consolidate a pilot study that we started in a valley in the eastern Pyrenees with experimental grazing exclusion and the tracking of a hundred cows with GPS/GSM technology. This combined and detailed analysis of the impacts of herbivory on the study communities will provide results applicable to the green transition (management and recovery of biodiversity) and the digital transition (livestock management).

At a regional scale, we will collect data in four Pyrenean Natura 2000 with spatial variability of livestock pressure, including pasture abandonment and vegetation encroachment, to analyze its influence on the spatial dynamics of the study communities. On a temporal scale, we will take advantage of the data that have been collected during the last three decades in twenty Pyrenean itineraries of the Catalan Butterfly Monitoring Scheme, to explore their temporal dynamics and the influence of the climate, of the different life strategies of each species, and the different models of livestock management. In parallel, we will explore the vegetation dynamics in the interdisciplinary frontier between ecology and mathematics for predicting the possible existence of critical phase transitions between habitats (from grasses to shrublands), generated by processes of facilitation, competition and herbivory.

The project will generate, on the one hand, relevant results for the ecology of populations and communities, and on the other, scientific evidence applicable to the management of socio-ecological systems and the conservation of alpine ecosystems. We intend to contribute to the international leadership of science in our country in the fields of ecology, socio-ecology and biodiversity conservation, and to generate both basic and applied scientific knowledge, through interdisciplinary research targeting green and digital transitions.

Researchers of the project:

Constantí Stefanescu, Andreu Ubach (Museu de Ciències Naturals de Granollers)

Federica Ravera (Universitat de Girona)

Tomás Lázaro (Universitat Politècnica de Catalunya (BarcelonaTech) · Departament de Matemàtiques)

Arantza Aldezabal (Euskal Herriko Unibertsitatea)

Meg Crofoot (Max Planck Institute of Animal Behavior, Constanz – Germany)

WATCH VIDEO: How a few cows move over one week

 

One Health PACT is a Dutch project to anticipate outbreaks of infectious diseases in humans and animals. High population density, with large numbers of farm animals in a wetland and canal landscape, and intense international and traveler trade, make the Netherlands a region vulnerable to outbreaks of infectious diseases. The objective of the project is to prepare the country for more frequent home outbreaks in Europe in an integrated way.

The One Healt PACT team focuses primarily on vector-borne diseases, primarily mosquitoes. In recent decades, international trade has led to the introduction of exotic mosquito spices in Europe, and climate change is favoring its spread throughout the continent. Invasive mosquitoes such as the tiger mosquito (Aedes albopictus) can transmit the viruses of diseases such as dengue, Zika or chikungunya. But also native mosquitoes, such as the common mosquito (Culex pipiens) can transmit viruses of tropical origin, mainly among birds, which occasionally can jump to humans.

The One Health PACT approach consists of four complementary and interactive pillars between them:

1. Ecosystem mapping
2. Prognosis and early detection
3. Evaluation of impact and severity
4. Interventions

The project’s ambition is to be prepared for arbovirus outbreaks in environments that are rapidly changing due to both climate change and landscape management and exploitation practices. Early detection of viruses and their risks can save lives.

 

The project consists of creating a Versatile Emerging Infectious Diseases Observatory (VEO) that allows to gather high quality information from which to develop early warning tools. The observatory will monitor emerging infectious diseases, as well as the appearance of bacterial resistance, in order to carry out a risk assessment.

VEO has the vision of being able to revolutionize the detection and prediction of threats to human and animal health derived from global changes. This revolution involves creating interdisciplinary teams, infrastructures and versatile technologies, working with open data and code, combining very diverse data (Big Data) and with data mining techniques to analyze a large volume of information to deduce patterns and be able to predict risks.

So, the project has seven specific defined objectives.

1. Develop a data platform that enables very diverse data integration, exchange between experts, and data mining. Tools to support interdisciplinary collaboration and international teams that make up the VEO system.
2.  Generate, update and validate inventories of genetic signatures associated with relevant pathogens, identify the relationship between genetic variations and the pathogenesis of a virus or bacterium in order to assess risk from genetic monitoring.
3. Integrate serological data from new antibody profiling technologies in the VEO database.
4. Evaluate the VEO system in five specific scenarios to ensure that it meets the needs of users and assess the functionality of the techniques and tools developed.
5. Develop a commitment to general needs rather than exploring the data, the challenges that come up, and finding solutions.
6. Develop a guide to the ethical, legal and social implications of collecting and integrating large amounts of epidemiological data, as well as the ethical and legal implications of health research aided by citizen science.

 

Many organisms form social systems, but most research does not consider collective processes to explain their ecological and evolutionary consequences for individuals and populations in stochastic environments. This application will help to produce a new hitherto unconsidered synthesis whereby I will integrate behaviour, social networks and movement with fitness variance and population dynamics in social organisms.

Novel analytical and technical methods now enable a generation of empirical and theoretical knowledge to quantify the influence of social networks and their emergent properties on collective motion. By applying these advances in the lab, in the field and in theory, I will proceed in three steps.

1. We determine, using lab and field data at a range of scales and life histories, how the features of social networks influence decision-making to drive searching trajectories for accessing resources in social species.
2. We assess how the attributes of searching trajectories in social groups relate to fitness parameters, and how collective movement, including group dispersal, influences population and metapopulation dynamics.
3. We build on previous steps to develop ecological theory for exactly decomposing how sociality and searching movement generate emergent properties and modulate life histories and population dynamics in variable environments.

This combined, interdisciplinary approach will lead to major advances in our understanding of critical transitions and other non-linearities due to feedbacks common to social systems, and will allow us building a unified social ecology for movement, life histories and population dynamics.

Periodic monitoring of biodiversity can boost the ecosystem capacity to cope with disturbance identifying risk factors, predicting phase shifts under future climate scenarios, and suggesting cost-effective management to reduce their impacts. This is particularly true in the ocean, where its out-of-sight nature may cause major alterations to pass unnoticed before damage is irreversible.

The worldwide biodiversity loss trend is also present in our coasts, where the dominance of habitat-forming macroalgae and their associated biodiversity have declined from the Bay of Biscay to the Canary Islands and is expected to do so in the near future. Identifying national biodiversity hotspots at high risk of collapse is critical to minimize the chances of losing our biodiversity. But Spain lacks the comprehensive and periodic biodiversity monitoring program needed to reach such goals.

DIVERSAT builds upon our previous MINECO grant, which identified national hotspots and their risk of collapse, to provide a novel five-year evolution of the biodiversity status of Spanish littoral reefs. A reliable biodiversity trend assessment can trigger mitigating actions before degradation affects our society.

DIVERSAT seeks funding to establish a regular biodiversity monitoring of the Spanish littoral reefs to make progress toward the first nation-wide, and multi-purpose monitoring program of these productive communities that will allow testing new spatial and temporal hypotheses. Our data will allow accurate quantification of many biodiversity metrics that contribute to multiple Aichi Targets of the Convention on Biological Diversity.

The project will specifically quantify multiple biodiversity indicators including resilience and risk of collapse to assess their evolution over the last five years. With extensive data and a variety of modeling techniques, we aim to create a predictive understanding of biodiversity responses of Spanish marine littoral reefs to climate change and also calculate for the first time a community thermal index that will allow tracking climate change effects on littoral reefs over the last five years and predicting climate change effects over future climate scenarios.

Spain stands at a crossroads. The expansion of Ae.albopictus throughout the Iberian Peninsula and the arrival of Ae.aegypti in the Canary Islands have increased the risk of serious outbreaks of dengue, chikungunya, or Zika, in Spain. With hundreds of imported cases already co-present with vectors, and autochthonous dengue transmissions confirmed in 2018, it is only a matter of time before Spain is faced with a serious public health crisis. Yet Spain lacks reliable information about disease risk patterns and the dynamics of potential outbreaks.

This project will fill this gap by bringing together experts in epidemiology, entomology, big data, movement ecology and socio-demography to build an innovative system that can harness the data revolution for public health preparedness. It will produce vital, comprehensive, actionable knowledge about mosquito-borne disease (MBD) risks and potential outbreaks in Spain.

It will fuse multiple big data sources and employ cutting edge modelling and infrastructure to:

1. Explore determinants and distribution of MBD risk
2. Illuminate links between social inequality and MBDs
3. Infer the role of human mobility in MBD risk
4. Ensure continuous model calibration and update
5. Deliver real-time models to public health agencies.

The system will give decision-makers the information they need, while also making raw data and open source code available for continuous improvement through open innovation.