Brian J. Stucky's research while affiliated with Florida Museum of Natural History and other places

... Additionally, after arriving in the Americas over 21k years ago (Bennett et al., 2021;Pigati et al., 2023), humans played an important role in modifying the distribution of fire and herbivore 'consumer regimes', by regulating the frequency, timing, and extent of both fire, via intentional burning, and herbivory, via management of wild and domestic herbivores (Nowacki et al., 2012;Roos et al., 2018). Beginning with the introduction of cattle by Europeans in the 16 th century (Delsol et al., 2023;Rouse, 1977), intensively managed and spatially constrained domestic livestock production systems have largely replaced free roaming herds of large herbivores in North America. Acknowledgement of widespread ecological impacts caused by altered fire patterns and herbivore communities has prompted calls for and motivated initiatives aimed at restoring ancient consumer regimes (Fuhlendorf et al., 2009;Lorimer et al., 2015). ...

... To date archaeological investigations in the archipelago have mainly focused on the earlier Indigenous societies, neglecting the subsequent periods (Arnay-de-la-Rosa 2009; González Marrero and Tejera Gaspar 2011;Mitchell 2023). Despite the key role of these islands in the development of animal translocation between continents (Delsol et al. 2022;López et al. 2013;McTavish et al. 2013;Olalde et al. 2015;Reitz 1992;Speller et al. 2013), local zooarchaeological research is basically limited to either Indigenous sites or sites from the fifteenth century corresponding to the period of contact between the Europeans and the Native populations (Castellano Alonso et al. 2016. Additionally, while historical written sources of the Modern Era of the Canary Islands provide valuable insights into human-animal interactions, they are often biased, limited in scope, or subject to interpretation. ...

... In addition, approaches have been developed to not only recognise objects in multimedia data sources, but also to differentiate by anomalies or other species-specific features such as plant or animal colours (e.g. Hantak et al., 2022;Perez-Udell et al., 2023). Ultimately, the ever-improving models used to generate ecological networks also help to turn information into knowledge. ...

... Some studies found opposite effects between daytime and nighttime temperatures across different natural ecosystems [14][15][16][17] , while others did not find such contrasting patterns 18,19 . Additionally, there are studies suggesting that urbanization, as measured using population density or urban fraction (UF), may have an equally substantial, or even a greater, impact on phenological shifts compared to UHI effects 20,21 , particularly in a climate-dependent context 22 . Confounding factors in urban areas may challenge the notion of treating the UHI effect on phenology in the same manner as the future warming environment 23 . ...

... Moreover, global warming may increase both the population growth and metabolic rates of insects. 5,59,60 This would be a challenge to sustainable approaches for meeting the increasing food demand because the most sustainable method would be increasing crop yields rather than reclaiming more land surface for crop production. 8,9 Thus, the emergence and spread of crop pests threatens global food security, 7 and soybean cultivated areas located in midlatitudes appear to be facing greater food security risks. ...

... Each photo includes detailed metadata: copyright status, location, uploader, time, and taxonomic classification. This diversity in image sources makes iNaturalist an excellent dataset for training AI models intended for real-world applications [37,24,7,3]. Despite its vast and diverse data, iNaturalist is not directly optimized for AI researchers: arranging this data for use in AI models like CLIP is not straightforward. ...

... In conclusion, AI has greatly affected medicine and biology, from detecting illnesses, medication discovery, and development to predicting protein structures and drug discovery. As AI technology matures, these areas will use it more, creating more inventive and efficient (Hamet & Tremblay, 2017;Hassoun et al., 2021). We offer some examples as illustrations, arranged in approximate order of increasing difficulty of implementation. ...

... Future analyses of extinct birds would greatly benefit from an integrative approach. In addition to classical morphological, chronological, and palaeoecological perspectives (e.g., Cooper et al. 1996;Tokita et al. 2017;Oswald et al. 2021), they should include genomic, epigenomic, and/or proteomic analyses of fossil and subfossil remains. Such approaches may in the future allow (1) reconstructing phylogenetic relationships and origins of extinct lineages, (2) distinguishing between true island-restricted radiations and independent waves of colonization, (3) estimating times of colonization and informing us of diversification processes, (4) determining the genetic diversity lost over time, and (5) uncovering genomic regions involved in the evolution of conspicuous and hidden "island syndrome" traits, suchas flightlessness and sedentarism, which could explain the effects of lowering or erasing gene flow among nearby populations favoring avian radiations (Burga et al. 2017;Horn et al. 2019). ...

... However, field-based phenological records documenting the onset and termination of phenophases across multiple species are limited in geographic or taxonomic scope (Sherry et al. 2011, Crimmins et al. 2013, Bock et al. 2014, and frequently focus on repeated observation of specific individuals rather than local populations. While modern observation networks such as the USA-NPN and iNaturalist have greatly broadened the spatial and taxonomic breadth of records capable of evaluating the timing of flowering onset, duration and termination, (Rosemartin et al. 2014, Pearse et al. 2019, Li et al. 2021, these data are limited in their temporal depth, and still exhibit significant taxonomic and spatial gaps. To date, this has limited our ability to assess climate-driven shifts in phenological synchrony across regions and taxa, highlighting the need for taxonomically and spatially extensive data sources that offer the capacity to estimate the duration of targeted phenophases. ...

... Following Semantic Web standards 80 , PKT-KG defines a KG as K = 〈T, A〉, where T is the TBox and A is the ABox. The TBox represents the taxonomy of a particular domain 81,82 . It describes classes, properties or relationships, and assertions that are assumed to generally hold within a domain (e.g., a gene is a heritable unit of DNA located in the nucleus of cells [ Fig. 7a]). ...