Abstract. Recent studies have shown that the Early EoceneClimatic Optimum (EECO) was preceded by a series of short-lived global warming events, known as hyperthermals. Here we present high-resolution benthic stable carbon and oxygen isotope records from ODP Sites 1262 and 1263 (Walvis Ridge, SE Atlantic) between ∼ 54 and ∼ 52 million years ago, tightly constraining the character, timing, and magnitude of six prominent hyperthermal events. These events, which include Eocene Thermal Maximum (ETM) 2 and 3, are studied in relation to orbital forcing and long-term trends. Our findings reveal an almost linear relationship between δ 13 C and δ 18 O for all these hyperthermals, indicating that the eccentricity-paced covariance between deep-sea temperature changes and extreme perturbations in the exogenic carbon pool persisted during these events towards the onset of the EECO, in accordance with previous observations for the Paleocene Eocene Thermal Maximum (PETM) and ETM2. The covariance of δ 13 C and δ 18 O during H2 and I2, which are the second pulses of the "paired" hyperthermal events ETM2-H2 and I1-I2, deviates with respect to the other events. We hypothesize that this could relate to a relatively higher contribution of an isotopically heavier source of carbon, such as peat or permafrost, and/or to climate feedbacks/local changes in circulation. Finally, the δ 18 O records of the two sites show a systematic offset with on average 0.2 ‰ heavier values for the shallower Site 1263, which we link to a slightly heavier isotopic composition of the intermediate water mass reaching the northeastern flank of the Walvis Ridge compared to that of the deeper northwestern water mass at Site 1262.

The Paleocene-Eocene Thermal Maximum (PETM) represents a ∼ 170 kyr episode of anomalous global warmth ∼ 56 Ma ago. The PETM is associated with rapid and massive injections of 13 C-depleted carbon into the ocean-atmosphere system reflected as a prominent negative carbon isotope excursion (CIE) in sedimentary components. Earth's surface and deep ocean waters warmed by ∼ 5 • C, of which part may have occurred prior to the CIE. However, few records document continental climatic trends and changes in seasonality have not been documented. Here we present the first high-resolution vegetation and paleoclimate reconstructions for the PETM, based on nearest living relative analysis of terrestrially derived spore and pollen assemblages preserved in an expanded section from the central North Sea. Our data indicate reductions in boreal conifers and an increase in mesothermal to megathermal taxa, reflecting a shift towards wetter and warmer climate. We also record an increase in summer temperatures, greater in magnitude than the rise in mean annual temperature changes, and a shift to a summer-wet seasonality. Within the CIE, vegetation varies significantly with initial increases in epiphytic and climbing ferns, and development of extensive wetlands, followed by abundance of Carya spp. indicative of broadleaf forest colonization. Critically, the change in vegetation we report occurs prior to the CIE, and is concomitant with anomalous marine ecological change, as represented by the occurrence of Apectodinium augustum. This suggests that amplifications of seasonal extremes triggered carbon injection.

The Paleocene-Eocene thermal maximum (PETM) represents a ~170 kyr episode of anomalous global warmth ~56 Ma ago. The PETM is associated with rapid and massive injections of ¹³C-depleted carbon into the ocean-atmosphere system reflected as a prominent negative carbon isotope excursion (CIE) in sedimentary components. Earth's surface and deep ocean waters warmed by ~5 °C, of which part may have occurred prior to the CIE. However, few records document continental climatic trends and changes in seasonality have not been documented. Here we present the first high-resolution vegetation reconstructions for the PETM, based on bioclimatic analysis of terrestrially-derived spore and pollen assemblages preserved in an expanded section from the Central North Sea. Our data indicate reductions in boreal conifers and an increase in mesothermal to megathermal taxa, reflecting a shift towards wetter and warmer climate. We also record an increase in summer temperatures, greater in magnitude than the rise in mean annual temperature changes. Within the CIE, vegetation varies significantly with initial increases in epiphytic and climbing ferns, and development of extensive wetlands, followed by abundance of Carya spp. indicative of broadleaf forest colonization. Critically, the change in vegetation we report occurs prior to the CIE, and is concomitant with anomalous marine ecological change, as represented by the occurrence of Apectodinium augustum. This suggests that amplifications of seasonal extremes triggered carbon injection

Monitoring of airborne pollen concentrations provides an important source of information for the globally increasing number of hay fever patients. Airborne pollen is traditionally counted under the microscope, but with the latest developments in image recognition methods, automating this process has become feasible. A challenge that persists, however, is that many pollen grains cannot be distinguished beyond the genus or family level using a microscope. Here, we assess the use of Convolutional Neural Networks (CNNs) to increase taxonomic accuracy for airborne pollen. As a case study we use the nettle family (Urticaceae), which contains two main genera (Urtica and Parietaria) common in European landscapes which pollen cannot be separated by trained specialists. While pollen from Urtica species has very low allergenic relevance, pollen from several species of Parietaria is severely allergenic. We collect pollen from both fresh as well as from herbarium specimens and use these without the often used acetolysis step to train the CNN model. The models show that unacetolyzed Urticaceae pollen grains can be distinguished with > 98% accuracy. We then apply our model on before unseen Urticaceae pollen collected from aerobiological samples and show that the genera can be confidently distinguished, despite the more challenging input images that are often overlain by debris. Our method can also be applied to other pollen families in the future and will thus help to make allergenic pollen monitoring more specific.

Airborne pollen monitoring is of global socio-economic importance as it provides information on presence and prevalence of allergenic pollen in ambient air. Traditionally, this task has been performed by microscopic investigation, but novel techniques are being developed to automate this process. Among these, DNA metabarcoding has the highest potential of increasing the taxonomic resolution, but uncertainty exists about whether the results can be used to quantify pollen abundance. In this study, it is shown that DNA metabarcoding using trn L and nrITS2 provides highly improved taxonomic resolution for pollen from aerobiological samples from the Netherlands. A total of 168 species from 143 genera and 56 plant families were detected, while using a microscope only 23 genera and 22 plant families were identified. NrITS2 produced almost double the number of OTUs and a much higher percentage of identifications to species level (80.1%) than trn L (27.6%). Furthermore, regressing relative read abundances against the relative abundances of microscopically obtained pollen concentrations showed a better correlation for nrITS2 (R 2 = 0.821) than for trn L (R 2 = 0.620). Using three target taxa commonly encountered in early spring and fall in the Netherlands ( Alnus sp., Cupressaceae/Taxaceae and Urticaceae) the nrITS2 results showed that all three taxa were dominated by one or two species ( Alnus glutinosa/incana , Taxus baccata and Urtica dioica ). Highly allergenic as well as artificial hybrid species were found using nrITS2 that could not be identified using trn L or microscopic investigation ( Alnus × spaethii , Cupressus arizonica , Parietaria spp.). Furthermore, perMANOVA analysis indicated spatiotemporal patterns in airborne pollen trends that could be more clearly distinguished for all taxa using nrITS2 rather than trn L. All results indicate that nrITS2 should be the preferred marker of choice for molecular airborne pollen monitoring.