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Reconstructing past vegetation can elucidate the timing, climate forcings, and biotic mechanisms of ecosystem change. Plant macro- and microfossils are traditionally used to study past vegetation but suffer from production and taphonomic biases, such as underrepresentation of important herbaceous vegetation components. Geochemical proxies can fill this gap, but carbon isotopes (δ13C) in isolation are unable to distinguish between structurally different C3 habitats, such as forests and grasslands. Thus, new geochemical methods to identify grassy C3 ecosystems are necessary. We present n-alkane chain length distributions of 209 plant specimens from two Kenyan C3-dominated ecosystems, representing a wide range of plant functional types (PFTs). We find that C3 PACMAD grasses produce exceptionally high abundances of long chain C33 and C35 n-alkanes (ACL =32.7, mean C33 +C35 relative abundance =0.69), unlike other C3 PFTs which produce low abundances of C33 and C35 (ACL =28.9–30.3, mean C33 +C35 relative abundance =0.0–0.21). This finding highlights the importance of measuring and reporting the C35 n-alkane. Our data further demonstrate that n-alkane distributions can serve as a proxy for some African C3 PACMAD grasses, offering a new paleoecological tool for distinguishing C3 vegetation types. 

This dataset comprises plant wax n-alkane chain length concentrations and C25-C35 relative abundances of 209 plant specimens from two Kenyan C3-dominated ecosystems, representing a wide range of plant functional types (PFTs). Plant samples were collected in 2018 from Mount Kenya National Park (n=122) and Kakamega National Forest (n=87). At Mount Kenya National Park, samples were collected along an elevational transect (~2400 m to ~3600 m above sea level) from five different ecotones: lower montane forest, bamboo zone, upper montane forest, ericaceous shrubland belt and Afroalpine moorland. Kakamega National Forest is ~1600m above sea level and samples were collected from an open glade, forest path edge, and closed canopy forest. All plant samples were identified to family level, most to genus or species level. Information on collection habitat, photosynthetic pathway, and plant functional type are included. The goal of this dataset was to assess n-alkane distributions for chemotaxonomic signals. Sample analysis took place at Lamont-Doherty Earth Observatory and Harvard University between 2022-2024. n-Alkane data were quantified using a gas chromatograph mass selective detector (GC-MSD) and a flame ionization detector (FID), and response factor corrections were calculated and applied to measured n-alkane peak areas in order to calculate corrected concentrations. The odd n-alkane C25-C35 concentrations were relativized to sum to 1 for the final relative abundance data. For more detailed information, please consult the associated manuscript on the n-alkane distributions and their chemotaxonomic significance: Tweedy et al., 2025. 

Equilibrium climate sensitivity (ECS) quantifies the amount of warming resulting from a doubling of the atmospheric CO2 forcing. Despite recent advancements in climate simulation capabilities and global observations, there remains large uncertainty on the degree of future warming. To help alleviate this uncertainty, past climates provide a valuable insight into how the Earth will respond to elevated atmospheric CO2. However, there is evidence to suggest that ECS is dependent on background climate warmth, which may interfere with the direct utilization of paleo-ECS to understand present-day ECS. Thus, it is important that a range of different climate states are considered to better understand the factors modulating the relationship between CO2 and temperature. In this study, we focus on three time intervals: the mid-Pliocene Warm Period (3.3 – 3.0 Ma), the mid-Miocene (16.75 – 14.5 Ma), and the early Eocene (~50 Ma), in order to sample ECS from Cenozoic coolhouse to hothouse climates. Here, we combine the Bayesian framework of constraining the ECS and its uncertainty with several published methods to estimate the global mean surface temperature (GMST) from sparse proxy records. This framework utilizes an emergent constraint between the simulated GMST changes and climate sensitivities across the model ensemble. For each time interval, we employ a combination of parametric and non-parametric functions, coupled with a probabilistic approach to derive a refined estimate. Preliminary results for the Pliocene indicate a GMST reconstruction of approximately 19.3°C, which is higher than previous estimates that were derived using only marine records. Using this estimate, we calculate an ECS that is also higher than previously published values, especially due to the inclusion of high-latitude terrestrial temperature records into our estimates. Intriguingly, using the consistent methodology, our calculated ECS for the early Eocene is lower than that of the mid-Pliocene. This result does not support an amplified ECS in hothouse climate, and points to a potentially important role of ice albedo feedback in amplifying the ECS in coolhouse climate. Ongoing work will apply the same methodology to the mid-Miocene and further investigate the source for the estimated ECS state dependency between these climate intervals. 

Abstract. The Oligocene (33.9–23.03 Ma) had warm climates with flattened meridional temperature gradients, while Antarctica retained a significant cryosphere. These may pose imperfect analogues to distant future climate states with unipolar icehouse conditions. Although local and regional climate and environmental reconstructions of Oligocene conditions are available, the community lacks synthesis of regional reconstructions. To provide a comprehensive overview of marine and terrestrial climate and environmental conditions in the Oligocene, and a reconstruction of trends through time, we review marine and terrestrial proxy records and compare these to numerical climate model simulations of the Oligocene. Results, based on the present relatively sparse data, suggest temperatures around the Equator that are similar to modern temperatures. Sea surface temperatures (SSTs) show patterns similar to land temperatures, with warm conditions at mid- and high latitudes (∼60–90°), especially in the Southern Hemisphere (SH). Vegetation-based precipitation reconstructions of the Oligocene suggest regionally drier conditions compared to modern times around the Equator. When compared to proxy data, climate model simulations overestimate Oligocene precipitation in most areas, particularly the tropics. Temperatures around the mid- to high latitudes are generally underestimated in models compared to proxy data and tend to overestimate the warming in the tropics. In line with previous proxy-to-model comparisons, we find that models underestimate polar amplification and overestimate the Equator-to-pole temperature gradient suggested from the available proxy data. This further stresses the urgency of solving this widely recorded problem for past warm climates, such as the Oligocene. 

Abstract Climate models require boundary condition information, such as vegetation and soil distributions because they influence the mean state climate, and feedbacks can significantly influence regional climate and climate sensitivity to CO₂forcing. Information about past distributions comes primarily from the paleobotanical record, which is often supplemented by a vegetation model to fill data gaps. For recent past periods such as the Pliocene, a quantitative suitability assessment of these vegetation model simulations is sufficient. However, the Miocene Climate Optimum spanning 16.9–14.7 Ma was the warmest period on Earth over the last ∼25 million years and models struggle to reproduce those conditions for the range of paleogeographies and CO₂concentrations tested, particularly at high latitudes. Here we bring together the Miocene modeling and data communities to update previous vegetation reconstructions used for climate modeling with a new regional approach that relaxes the requirement for a single model simulation to be used, blending instead simulations forced by different paleogeographies and CO₂concentrations. This ensures the simulated vegetation is first, and foremost, consistent with the paleorecord and provides a baseline for future comparisons. The reconstruction shows global increases in forest cover at all latitudes as compared to today and extensive C₃grasslands across the high northern latitudes. Data gaps at high latitudes are filled with vegetation models forced by higher CO₂concentrations than were required at lower latitudes consistent with the inability of current models to simulate Miocene high latitude warmth. 

Abstract Earth's hydrological cycle is expected to intensify in response to global warming, with a “wet‐gets‐wetter, dry‐gets‐drier” response anticipated over the ocean. Subtropical regions (∼15°–30°N/S) are predicted to become drier, yet proxy evidence from past warm climates suggests these regions may be characterized by wetter conditions. Here we use an integrated data‐modeling approach to reconstruct global and zonal‐mean rainfall patterns during the early Eocene (∼56–48 million years ago). The Deep‐Time Model Intercomparison Project (DeepMIP) model ensemble indicates that the mid‐ (30°–60°N/S) and high‐latitudes (>60°N/S) are characterized by a thermodynamically dominated hydrological response to warming and overall wetter conditions. The tropical band (0°–15°N/S) is also characterized by wetter conditions, with several DeepMIP models simulating narrowing of the Inter‐Tropical Convergence Zone. However, the latter is not evident from the proxy data. The subtropics are characterized by negative precipitation‐evaporation anomalies (i.e., drier conditions) in the DeepMIP models, but there is surprisingly large inter‐model variability in mean annual precipitation (MAP). Intriguingly, we find that models with weaker meridional temperature gradients (e.g., CESM, GFDL) are characterized by a reduction in subtropical moisture divergence, leading to an increase in MAP. These model simulations agree more closely with our new proxy‐derived precipitation reconstructions and other key climate metrics and imply that the early Eocene was characterized by reduced subtropical moisture divergence. If the meridional temperature gradient was even weaker than suggested by those DeepMIP models, circulation‐induced changes may have outcompeted thermodynamic changes, leading to wetter subtropics. This highlights the importance of accurately reconstructing zonal temperature gradients when reconstructing past rainfall patterns.