Bio

         Daniel earned a bachelor’s degree in Biology at the University of Barcelona. After that, he decided to expand his fieldwork experience by volunteering in marine conservation projects around the world. He first collaborated with CIRCE and Associació Cetàcea, two associations involved in the protection of marine mammals. Later on, Daniel went to Costa Rica where he volunteered for two conservation organizations (PRETOMA and Estación las tortugas) aiming at the protection of sea turtles. During these nine months, his tasks included beach patrolling, collecting eggs and data, relocating and monitoring nests, and environmental education. These experiences reinforced my willingness to study and work in the field of marine biology and conservation. For all those reasons, in 2014 he decided to enroll in the master’s degree in Oceanography at the University of Barcelona.

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​            This master’s degree allowed him to obtain a lot of knowledge related to marine biology and allowed me to meet two great scientists and supervisors of my master’s thesis Isabel Palomera and Marta Coll. Besides their scientific supervision, they transmitted their passion for marine conservation and fishery management. After graduating with a Master of Science in Oceanography and Marine Management at the University of Barcelona in 2016, he started working as a research assistant at the Institute of Marine Sciences (ICM-CSIC) and the Ecopath International Initiative (Barcelona, Spain) under the supervision of Marta Coll. While there, he was involved in three European projects named SafeNet, KELPEX, and MERCES in which he took part in ecosystem modeling groups with Chiara Piroddi, Jeroen Steenbeek, and Marta Coll. For the SafeNet project, I developed several ecosystem models (Ecopath with Ecosim, EwE) representing a fisheries restricted area and marine protected areas in the Northwestern Mediterranean Sea to evaluate their ability to support fisheries and ecosystem recovery. During this project, Daniel wrote a protocol for calculating the production and consumption rates of marine species and built a diet database for Mediterranean marine species. For the KELPEX and the MERCES projects, he built a EwE model representing an Arctic deep-sea ecosystem associated with kelp detritus exports to assess the role of kelp detritus on the deep-sea ecosystem and to assess the potential effects of plausible future trajectories of change for major drivers in the area. In addition, he participated in the sampling survey that was carried out in the Norwegian Sea (Malangen fjord) and processed samples for stable isotopes analyses at the Arctic University of Norway (Tromsø, Norway). Combined, these projects produced six publications, four of which he was the lead author of.

              From 2019 to 2022, he worked as a graduate research assistant at the University of Florida under the supervision of David Chagaris while working on my PhD titled “Spatiotemporal ecosystem dynamics on the West Florida Shelf: Prediction, validation, and application to red tides and stock assessment”. His research supported the project entitled “Ecosystem Modeling to Improve Fisheries Management in the Gulf of Mexico”, funded by the NOAA Restore Act Science Program. The main goal of this project was to formally integrate information on ecosystem stressors and predator-prey interactions into the fisheries assessment and management process of the Gulf of Mexico. He performed spatial data analysis and batch processing of multiple survey datasets from the Gulf of Mexico including the SEAMAP bottom trawl, NMFS bottom longline, and the NMFS-FWC trap and camera survey. Daniel developed, fitted, and evaluated multiple species distribution (VAST, GLM, GLMM, delta-GLM, and GAM), statistical catch-at-age (Stock Synthesis and ADMB), ecosystem (Ecopath with Ecosim), and spatiotemporal ecosystem models (Ecospace). Using Ecospace, he also quantified the red tide mortality rate of gag grouper (Mycteroperca microlepis) on the West Florida Shelf (WFS). This required developing and testing new mortality functions in the Ecospace software, validating predictions, and novel parallel processing of Ecospace simulations using R. In addition, he created an R Shiny app (RedTideVIS; https://redtidevis.shinyapps.io/redtideapp/) to communicate estimated red tides impacts on the WFS region and the associated uncertainty to stakeholders. The Ecospace model demonstrated that current survey designs in the WFS are not adequate to detect the effects of episodic mortality events because of the spatiotemporal localized nature of such events. Once the Ecospace model was fitted and validated, the model was used as an operating model for the WFS ecosystem to simulate data for Stock Synthesis and explore multiple interpretations of natural mortality from episodic events. Finally, he fitted additional VAST models to explore spatiotemporal aspects of red tides on the WFS and spatiotemporal trends of multiple species of ichthyoplankton in the Bering Sea. The estimated mortality rates for gag were considered in a stock assessment sensitivity run and near-real-time estimates of red tide mortality in 2021 were used in the final projection scenarios for catch advice, marking the first time an ecosystem model was used in actual management advice in the Gulf of Mexico. His dissertation produced four publications (in preparation), three of which I was the lead author of.

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