These are the main topics of my research projects. Click them to see the details.
Soil biotic interactions
In terrestrial ecosystems, the decomposition of leaf litter by the detrital food web returns around 50% of net primary production to the soil, increasing nutrient availability for plants. Soil fauna is an important driver that alters decomposition by fragmenting litter and altering soil microbial communities.
Climate also plays an essential role in decomposition because temperature and water availability affect many biological processes linked to litter decomposition. For instance, water availability affects the distribution and abundance of most soil invertebrates. This has strong implications for the occurrence of soil biotic interactions such as predation, competition, mutualism and facilitation among others. Water availability is therefore an important factor that explains the patterns of interactions in some soil food webs and, ultimately, leaf litter decomposition.
During my PhD I conducted observational, field and laboratory experiments to study the role of water availability on shaping soil predator-prey interactions and the composition of soil food webs. The main goals of this research were i) to describe the heterogeneous horizontal soil water distribution on the forest floor and its implications for the spatial distribution of soil fauna, ii) to investigate the underlying mechanisms by which water availability affects biotic interactions, and iii) to conduct field experiments to stress the importance of water availability for the spatial distribution and interaction of soil organisms.
Understanding how animals make use of environmental information is of particular importance for designing effective pest management strategies. Different kinds of stimuli can be used to disrupt the movement of pests and thereby protect the resource by making it harder to locate. Examples include the design of stimuli that mimic a resource, trap crops or push-pull systems. Sticky-traps, have proved to be highly effective in controlling populations of pests like Rhagoletis pomonella. However, such methods are currently underexploited, presumably because they require a good understanding of the movement behavior of the pest.
During my thesis I collaborated with researches from the University of Kentucky to develop a cellular automata model to understand the movements of the Japanese beetle –Popillia japonica– through a homogeneous soybean crop. This beetle is an important pest species that feeds on more than 300 species of plants causing significant economic loss, especially in the US. Our study linked the movements of the beetle to observed damage patterns in a soybean crop and designed effective pest management strategies to reduce crop damage.
Additionally, in collaboration with researchers from the French Research Institute on Insect Biology - IRBI (Tours, France) and the Institute of Ecology – UNAM (Mexico), I studied the movement of the apple maggot –Rhagoletis pomonella– in heterogeneous environments (tree branches) and estimated both the perceptual range and the attraction strength of stimulus. This approach is a step forward in understanding the movement of a pest in the presence of an artificial fruit. It can be used to extract the intrinsic, distance-dependent strength of attraction of a stimulus source as well as its modulation by the environment, which should lead to the design of better pest management strategies.
Insects have a tremendous potential as a source of food and feed. In fact, insect mass-rearing is starting to play an important role as an alternative protein source for animals and humans. Compared to the production of conventional livestock, insects have higher feed conversion efficiencies, require less land and are expected to use less water, which, in principle, makes them more environmentally friendly. Additionally, insects can be feed by a variety of agro industrial by-products. The use of insects as protein source for animals could be particularly relevant for industry such as aquaculture. Due to the overfishing of the oceans the aquaculture feed industry is noticing a decrease of fishmeal availability and an increase of its price, which is triggering the search of alternatives for the traditional aquaculture feeds. Insects are the natural diet of many fish, and could be a good alternative of fishmeal.
Insect mass-rearing also plays an important role in some pest management strategies such as the augmentative biological pest control. In this pest management strategy, the natural enemies of pests are produced massively and released in infested crops to reduce pest damage.
Currently I am working at Ynsect, a biotech company, to develop novel insect mass-rearing methods that can be automatized and scaled-up in order to make insect production less labor intensive. I also work to intensify insect production and make the mass-rearing less costly.
Animal movement determines encounter rates between organisms, playing an important role for biotic interactions and many ecological processes such as population dynamics, population genetics and the spread of diseases. Patterns of animal movement are determined by the velocity, the sinuosity of the movements and the taxis towards certain areas, and many animals are capable of adjusting some movement parameters to optimize encounter rates.
During my PhD I studied the ecological and evolutionary consequences of animal movement for biotic interactions. To study animal movement I designed different experimental set-ups to measure the movement of soil fauna in the laboratory and in the field and developed three different models of animal movement that I detail below.
In collaboration with the University of Kentucky, I developed a cellular automata model to study the movement of Japanese beetles. This model was based in an Eulerian approach, which describes the expected pattern of space use by a population. The other two models were based in a Lagrangian approach, which describes the detailed movement of individuals. The first one –in collaboration with the University of Split (Croatia)–, was a spatially-explicit agent-based model to study how perceptual abilities of animals affect their movement and encounter rates. The model was constructed using C++ and can accommodate different species and a large number of individuals. The second one –in collaboration with the French Research Institute on Insect Biology - IRBI (Tours, France) and the Institute of Ecology UNAM (Mexico)–, was a model of random walks in graph to study the movement of flies in structured complex environments such as the branches of a tree. This is a powerful method to model the movement of animals in structured environments, where the branches of trees were represented as a graph structure.
It is well known that ecological changes have important consequences for evolution, and that, at the same time, these evolutionary changes could influence several ecological processes –e.g. food web structure, population dynamics or the composition of communities– if significant phenotypic changes occur.
Part of my research is focused to understand how ecology shapes the evolution of key life history traits such as egg size and number. Specifically, I worked on how animal movement and body size, which are related to encounter and predation rates, respectively, could have influenced the evolution of egg size and egg number in generalist predators. In collaboration with the Netherlands Institute of Ecology I also participated in a research project to study how major trait changes, i.e. trait decay or loss, influence the divergence of life history traits.
Data science is a field that emerges at the intersection of areas such as statistics, computer science, database management and other related fields. Yet, some researchers consider the term data science a synonym of statistics. The volume of data that is generated over the world is exploding, and often, only a very small proportion of all data is analyzed. Data science has gained significant interest over the past years because it provides solutions to face this huge amount of data. The process to analyze and learn from data include data collection, manipulation and analysis, and communication of the results. Typically, some of those steps, if not all, involve writing code in some programming language.
I have been interested in statistics and data science since I started doing research, and as time passes, these activities are gaining more place in my daily work activities. Nowadays I use R to tell stories with data for the agro industry sector. For this I develop R packages for data mining and predictive analytics, and I work on a variety of data science topics including statistical modeling, data visualization methods and machine learning to analyze biological datasets.