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From data to discovery: Understanding the tetrapod Wallacean shortfalls through time

Grant number: 23/14506-5
Support Opportunities:Scholarships in Brazil - Post-Doctoral
Effective date (Start): May 01, 2024
Effective date (End): April 30, 2026
Field of knowledge:Biological Sciences - Ecology - Applied Ecology
Principal Investigator:Mathias Mistretta Pires
Grantee:Matheus de Toledo Moroti
Host Institution: Instituto de Biologia (IB). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil

Abstract

Biodiversity is essential for ecosystem functioning and human well-being. However, global knowledge of biodiversity is still incomplete and only 13-18% of all living species had been formally discovered. To worsen this scenario, our knowledge on the geography of known species is also limited (Wallacean shortfall), which can endanger the conservation and sustainable use of natural resources. In a planet with increasing changes, it is necessary to understand where the greatest limitations in our biodiversity knowledge are before it is too late. This project aims to investigate factors able to accelerate the knowledge on global tetrapod's geography, and project the expected change in knowledge shortfalls based on historical trends of knowledge accumulation. Specifically, we will address four main questions: (1) identify biological, geographical and socioeconomic factors (if any) influencing the time of geolocation of tetrapod species; (2) map regions where knowledge accumulation has been slower (knowledge accumulation lag); (3) identify the priority regions and clades for field sampling based on projected trends of knowledge accumulation; and (4) detect the regions that are simultaneously the most affected by Wallacean knowledge lags and estimates of global change. To address these issues, we will initially collect and harmonize expert range maps from IUCN with dated occurrences from GBIF. We will implement time-to-event models to elucidate the determinants of the time-to-geolocation for each species and spatial sample. In computing the average geolocation time across administrative units and ecoregions, we will be able to rank regions with persistent knowledge gaps through time. We will also consider future projections, including potential threats like climate change, to identify priority areas where knowledge will accumulate slowly and where extrinsic threats may have a significant impact. This comprehensive method will help us understand how these predictors affect the accumulation of knowledge about the geographic distribution of tetrapods, as well as what the future scenarios are. Key impacts of this work include advancing the training of new data scientists in biodiversity and guiding data-driven conservation strategies.

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