Pollen identification is necessary for several subfields of geology, ecology, and evolutionary biology. However, the existing methods for pollen identification are laborious, time-consuming, and require highly skilled scientists. Therefore, there is a pressing need for an automated and accurate system for pollen identification, which can be beneficial for both basic research and applied issues such as identifying airborne allergens. In this study, we propose a deep learning (DL) approach to classify pollen grains in the Great Basin Desert, Nevada, USA. Our dataset consisted of 10,000 images of 40 pollen species. To mitigate the limitations imposed by the small volume of our training dataset, we conducted an in-depth comparative analysis of numerous pre-trained Convolutional Neural Network (CNN) architectures utilizing transfer learning methodologies. Simultaneously, we developed and incorporated an innovative CNN model, serving to augment our exploration and optimization of data modeling strategies. We applied different architectures of well-known pre-trained deep CNN models, including AlexNet, VGG-16, MobileNet-V2, ResNet (18, 34, and 50, 101), ResNeSt (50, 101), SE-ResNeXt, and Vision Transformer (ViT), to uncover the most promising modeling approach for the classification of pollen grains in the Great Basin. To evaluate the performance of the pre-trained deep CNN models, we measured accuracy, precision, F1-Score, and recall. Our results showed that the ResNeSt-110 model achieved the best performance, with an accuracy of 97.24%, precision of 97.89%, F1-Score of 96.86%, and recall of 97.13%. Our results also revealed that transfer learning models can deliver better and faster image classification results compared to traditional CNN models built from scratch. The proposed method can potentially benefit various fields that rely on efficient pollen identification. This study demonstrates that DL approaches can improve the accuracy and efficiency of pollen identification, and it provides a foundation for further research in the field.

The Deepwater Horizon (DWH) blowout and oil spill began on April 20, 2010 in the northern Gulf of Mexico (NGOM) deep sea (1525 m). Previous studies documented an impacted area of deep-sea floor totaling 321 km² and were based on taxonomy at the macrofauna family level and the meiofauna major taxonomic level. In the present study, finer taxonomic resolution of the meiofauna community was employed, specifically harpacticoid copepod family biodiversity. Severe or moderate impacts to harpacticoid family biodiversity were observed at 35 of 95 sampling stations, covering an estimated area of 2864 km², 8.9 times greater impacted area than previously reported. Sensitive and tolerant harpacticoid families were observed in the impact zone. The present study greatly expands the understanding of DWH deep-sea impacts in 2010 and demonstrates that the harpacticoid family-level response is the most sensitive indicator (reported to date) of this oil spill pollution event.

The progressive closure of the Neotethys Ocean had a profound impact on the ocean-climate system during the Cenozoic. In this perspective, Turkey represents a key area for studying the climate evolution during the Eocene, because it was located at the gateway between the Neotethys and the Atlantic Ocean. Here, we present a high-resolution integrated magnetobiostratigraphic record of a new middle Eocene sedimentary section from the Elazığ Province, eastern Turkey. The continuous, undisturbed, and undeformed sedimentary record, together with preserved geomagnetic signal and fossil assemblages, allows the establishment of a detailed age model, which spans from the upper part of chron C19n.1r to the base of chron C17n.1n (42.4−37.8 Ma). Field observations and paleontological and paleomagnetic data show that the section has not been affected by the widespread tectonic deformation that characterizes the region. We suggest that the magnetostratigraphically and biostratigraphically calibrated Baskil section represents a new, outstanding shallow- to deep-marine sequence where paleoceanographic and paleogeographic studies can be conducted to understand the middle Eocene climate evolution.

In the last three decades, benthic foraminiferal ecology has been intensively investigated to improve the potential application of these marine organisms as proxies of the effects of climate change and other global change phenomena. It is still challenging to define the most important factors affecting foraminiferal communities and derived faunistic parameters. In this study, we examined the abiotic-biotic relationships of foraminiferal communities in the central-southern area of the Adriatic Sea using modern machine learning techniques. We combined gradient forest (Gf) and structural equation modeling (SEM) to test hypotheses about determinants of benthic foraminiferal assemblages. These approaches helped determine the relative effect of sizes of different environmental variables responsible for shaping living foraminiferal distributions. Four major faunal turnovers (at 13–28 m, 29–58 m, 59–215 m, and >215 m) were identified along a large bathymetric gradient (13–703 m water depth) that reflected the classical bathymetric distribution of benthic communities. Sand and organic matter (OM) contents were identified as the most relevant factors influencing the distribution of foraminifera either along the entire depth gradient or at selected bathymetric ranges. The SEM supported causal hypotheses that focused the factors that shaped assemblages at each bathymetric range, and the most notable causal relationships were direct effects of depth and indirect effects of the Gf-identified environmental parameters (i.e., sand, pollution load Index–PLI, organic matter–OM and total nitrogen–N) on foraminifera infauna and diversity. These results are relevant to understanding the basic ecology and conservation of foraminiferal communities.

Extinction patterns, paleobathymetric inferences, and paleoenvironmental changes based on benthic foraminifera were investigated across the Cretaceous/Paleogene (K/Pg) boundary at the Galanderud section (Northern Alborz, Iran), which contains one of the most continuous and expanded K/Pg transitions in the eastern Tethys. On the basis of benthic foraminiferal taxa abundance and distribution, an outer neritic to uppermost bathyal paleo-depositional setting is inferred. In addition, benthic foraminiferal assemblages and planktic/benthic ratios do not indicate any major change in relative sea level during latest Maastrichtian-early Danian time. Changes in benthic foraminiferal assemblages, morphotypes, diversity, heterogeneity, and benthic foraminiferal oxygen index, coupled with statistical analyses, define three intervals. In the first interval (uppermost Maastrichtian Plummerita hantkeninoides Zone), benthic foraminiferal assemblages are moderately to well preserved and highly diverse, with a combination of epibenthic and endobenthic taxa indicating stable, mesotrophic to weakly eutrophic, normal marine conditions. A major change in benthic foraminiferal assemblages at the K/Pg boundary defines a second interval (basal Danian Guembelitria cretacea and lower part of Parvularugoglobigerina eugubina Zones) that is marked by a decrease in the endobenthic morphogroups as well as a decrease in diversity, heterogeneity, genus and species richness. This second interval denotes highly oligotrophic conditions and a collapse in productivity and food availability due to the extinction of some primary producers, with the exception of the three chalk beds representing short-lived blooms of calcareous dinoflagellates. Benthic foraminifera do not show significant extinction at the end of the Cretaceous at this section with only about an 8% loss of species. Additionally, the abundance of some opportunistic species, including Cibicidoides pseudoacutus and Tappanina selmensis, may reflect instability in the benthic foraminiferal assemblages. The third interval (middle-upper part of the Pv. eugubina Zone) is characterized by the dominance of epibenthic morphogroups (up to 70% of the assemblages) with a partial recovery of endobenthic groups. The characteristics of the benthic foraminiferal assemblages indicate that the flux of food to the benthos had not fully recovered during the early Danian.