Historical variations of surface temperature in relation to anthropogenic warming has been extensively studied to understand and explain changes in the contemporary climate and to estimate future impacts of climate．Inoue and others (in press) reported 228-year records of SST and salinity based on Sr/Ca and d¹⁸O analyses with monthly time resolution in Porites coral collected from Bicol, the south of Luzon, Philippines. From the record, we investigated the relationship between the reconstructed temperature and the volcanic eruptions in late 18^th and early 19^th centuries. There were three great famines during the Edo period (1603-1868), almost corresponding to the Little Ice Age in Japan. Of these, the two were Tenmei-famine in 1782-88 and Tempo-famine in 1833-1837(1839). Both famines killed more than one million people out of a population of 30 million at the time. Our reconstructed SST anomaly fluctuated between -1.5 degree and 1.0 degree. The age model may have the age error of 1 to 3 years before around 1885. Large minima occurred in 1785-1789, 1815-1819, 1822-25, 1827-1830, 1834-1835, and 1843-45. Although Laki eruption, Iceland in 1783 has not been described as large eruption in previous studies, their impact on climatic conditions around the Northern Hemisphere and the globe was widely reported. Local eruption of Asama, Japan in 1783 released volcanic ash over eastern part of Japanese islands, In addition, El Nino event, which often cooled down Japanese islands, occurred around those days. These factors could have been responsible for the coldest anomaly in 1785-1789 recorded in our coral samples. After Tambora eruption in 1815, sharp cooling of around 2.0˚C was observed in our coral sample and almost all over the world. However, this world-scale cooling event have no or little influence on the climate in Japanese islands based upon the historical documents and agriculture records. This indicates that there are areas that do not become exceptionally cold, even by major volcanic eruptions. Large eruption of Galunggung in 1822 brought appreciable degree of cooling anomaly in our coral record. Just after Agung exploded largely in 1843, reconstructed SST significantly dropped. This might be also influenced by another large eruption of Cosiguina in Nicaragua, central America. Cold climate was reported in Japan, New York in USA, Copenhagen, UK in 1840s. It was most likely global in scale in the northern hemisphere.

How to cite: kawahata, H., Inoue, M., Chihara, M., Siringan, F. P., and Suzuki, A.: Coral record from Bicol in the Philippines in 1770-1850 reveals volcanic cooling, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1833, https://doi.org/10.5194/egusphere-egu23-1833, 2023.

Scaling fluctuation analyses of the marine animal diversity, extinction and origination rates based on the Paleobiology Database occurrence data have opened new perspectives on macroevolution, supporting the hypothesis that the environment (climate proxies) and life (extinction and origination rates) are scaling over the “megaclimate” biogeological regime (from ≈ 1 Myr to at least 400Myrs).   In the emerging picture, biodiversity is a scaling “cross-over” phenomenon being dominated by the environment at short time scales and by life at long times scales with a cross-over at ≈40Myrs.  These findings provide the empirical basis for constructing the Fractional MacroEvolution Model (FMEM), a simple stochastic model combining destabilizing and stabilizing tendencies in macroevolutionary dynamics.  The FMEM is driven by two scaling processes: temperature and turnover rates. 

Macroevolution models are typically deterministic (albeit sometimes perturbed by random noises), and based on integer ordered differential equations.  In contrast, the FMEM is stochastic and based on fractional ordered equations.   Stochastic models are natural for systems with large numbers of degrees of freedom and fractional equations naturally give rise to scaling processes. 

The basic FMEM drivers are fractional Brownian motions (temperature, T) and fractional Gaussian noises (turnover rates E₊) and the responses (solutions), are fractionally integrated fractional Relaxation processes (diversity (D), extinction (E), origination (O) and E_- = O - E).  We discuss the impulse response (itself a model for impulse perturbations such as bolide impacts) and derive the full statistical properties including cross covariances.  By numerically solving the model, we verified the mathematical analysis and compared both uniformly and irregularly sampled model outputs to paleobiology series. 

The six series (T, E₊, D, E_-, O, E) had fluctuation statistics that varied realistically with time scales Δt (lags) over the observed range (≈3 Myrs to ≈ 400 Myrs).  In addition, the 15 pairwise fluctuation correlations (of the six variables) as functions of Δt were also very close to observations even though only two correlations were specified in the model (TE₊and TD).  The ability to simulate the effects of irregular temporal sampling was important since model – data agreement was much better with realistic (irregular) sampling than with uniform sampling.  Although the model could easily be made more complex, this may not be warranted until much higher resolution series become available.

How to cite: Lovejoy, S. and Spiridinov, A.: The Fractional Macro Evolution Model: A simple quantitative scaling macroevolution model, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4446, https://doi.org/10.5194/egusphere-egu23-4446, 2023.

Geohistorical records, either stratigraphic sections, boreholes, ice cores, or archaeological sites, are inherently complex. Despite their limitations, the high-dimensional and spatiotemporally resolved data retrieved from individual geohistorical records allow for evaluation of past biotic responses to natural and human-induced environmental changes. Network analysis is becoming an increasingly popular alternative for modelling the dynamics of geohistorical data. However, the complexity of geohistorical data raises questions about the limitations of standard network models widely used in paleobiology research. They risk obscuring large-scale patterns by washing out higher-order node interactions when assuming independent pairwise links. Recently introduced higher-order representations and models better suited for the complex relational structure of geohistorical data provide an opportunity to move paleobiology research beyond these challenges. Higher-order networks can represent the spatiotemporal constraints on the information paths underlying geohistorical data, capturing the high-dimensional patterns more accurately. Here we describe how to design higher-order network models of geohistorical data, address some practical decisions involved in modeling complex dependencies, and discuss critical methodological and conceptual issues that make it difficult to compare results across studies in the growing body of network paleobiology. We illustrate multilayer networks, hypergraphs, and varying Markov time models through case studies on the fossil record from continental shelf ecosystems and delineate future research directions for current challenges in the emerging field of network paleobiology.

How to cite: Rojas, A., Holmgren, A., Neuman, M., Edler, D., Blöcker, C., and Rosvall, M.: A natural history of networks: Modelling higher-order interactions in geohistorical data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6870, https://doi.org/10.5194/egusphere-egu23-6870, 2023.

The biodiversity is the fundamental aspect and transitive measure of biota and the evolutionary process itself. The biodiversity is usually understood as the diversity of morphological or structural types, and also as the number of taxa (species, genera, families etc.) or branches of different ranks in evolutionary trees or networks. The biodiversity is hierarchical and universal feature of biological systems. Despite its conceptual simplicity, the origins and patterns of variability of diversity, except the fact that they are based on the evolutionary process, are rather hardly comprehensively understood. Therefore, the determination of origins, and the dynamics of biodiversity through the space and time, is one of the most fundamental open questions of biology.

                             The theory of evolution reveals a number of possibilities on how biodiversity can change, and also predicts patterns which underlie the mechanism: if the biodiversity is autonomous and self-regulating process, or if opposite is true – the biodiversity is a driven variable dependant on many varying Earth system, and possibly astrophysical components. One of the most promising approaches in characterizing the dynamics of biodiversity, and discriminating between the underlying causes of the dynamics, is the analysis of scaling.

                             The spatial scaling of biodiversity is a well developed field of science. The dependence of species richness on the geographical area is described by power laws. The values of parameters could be interpreted with respect to possible controlling genealogical and ecological mechanisms of evolution. The scaling of biodiversity in space, also suggests the scaling of biodiversity as a function of time scale. The scaling is time scale symmetry which connects the large and small scales, and it reveals the uniformity of a mechanism in a scaling range. Presented approach allows the summarization of macroevolution in very simple terms.

                             Here we present a case of global marine animal biodiversity, and based on the revealed crossover-like time scaling pattern, we suggest that two competing time symmetric scaling mechanisms, with opposite effects on biodiversity (stabilizing versus destabilizing), are responsible for the evolution of the biota at the eon scale. The presented results can serve as a null model in understanding global evolution, and also can serve in sharpening and strengthening of our intuitions in exploring and explaining macroevolutionary patterns.

                             The research was supported by the project S-MIP-21-9 “The role of spatial structuring in major transitions in macroevolution”.

How to cite: Spiridonov, A., Lovejoy, S., and Balakauskas, L.: Framing origins and dynamics of biodiversity in the paradigm of space and time scaling, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7943, https://doi.org/10.5194/egusphere-egu23-7943, 2023.

Feathers are key innovations that underpin the evolutionary success of birds, and biologists have achieved a solid understanding of modern feather types and their functions. Nonetheless, the unexpected recent discoveries of several specialized feather morphologies in extinct birds and related dinosaurs, challenges our views of the overall evolution of feathers. Such discoveries raise large evolutionary questions in a wider group than simply birds (i.e., dinosaurs as well as pterosaurs). These are related, for instance, to the initial function of feathers, subsequent feather diversification and functions, and potential links between such evolution and external factors. We have differentiated and inventoried fossil feather types based on their general morphological structure, and coded these as traits that relate to feather functions. We analyse the dataset through computational phylogenetic comparative methods, including ancestral state reconstructions, to identify the points of origin for each feature and estimate patterns and rates of evolution. Monofilamentous integumentary structures appear synapomorphic to Avemetatarsalia. A loss of monofilamentous integumentary structures occurred within Pennaraptora. While the presence of pennaceous feathers is synapomorphic for Pennaraptora, the presence of pennaceous feathers on the hindlimbs is a synapomorphy of Paraves. There is greater complexity, however, in feather evolution, with uncertainty over convergence and uniqueness of some feather types not seen in modern birds. The analysis allows some connection from feather morphology evolution to the sequence of regulatory gene switches in modern feather ontogenetic development, but the fossils suggest a richness of evolution not directly seen in studies of feather evo-devo.

How to cite: Cockx, P. and Benton, M.: Exploring evolution of feather function in early birds and dinosaurs, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8513, https://doi.org/10.5194/egusphere-egu23-8513, 2023.

Bretskyan hierarchy of eco-evolutionary entities is a useful theoretical concept that defines hierarchies of communities of species which reside in the same geographical space and are tied together by ecological interactions and evolutionary history. Bretskyan hierarchy can be employed to define and track the evolving hierarchy of bioregions, allowing all sorts of (paleo)biogeographical investigations to be carried out: from finding the causes why bioregions split or fuse and how this happens at many spatial scales, ie. what drives the internal structure of bioregions in Bretskyan hierarchy. Unfortunately, methodical applications of this concept are challenging due to the hybrid nature of Bretskyan hierarchy entities and fuzziness of their boundaries.

In order to help solve the presented problem of explicit subdivision of contiguous spatial regions, which are in our understanding the units of the Bretskyan hierarchy, we propose a new method, within the newly developed R package “HespDiv” which presents a range of functionalities for the determination of spatial structures/bioregions. The method uses fossil taxa distribution data to subdivide a provided territory into hierarchically related (each bioregion is a strict sub-set of larger bioregion) and topologically contiguous bioregional units. It produces split-lines which are used to subdivide bioregions. This subdivision can be done by employing linear or nonlinear divisor lines inside predetermined area polygons. In a latter case, the inferred bioregions can obtain more realistic shapes. The application of “HespDiv” method to Miocene fauna from the contiguous United States was performed in order to demonstrate the potential of the method. Morisita-Horn similarity index was used to measure differences between fossil taxa communities. The results revealed 25 distinct, topologically contiguous and hierarchically related bioregions had the structure dominated by longitudinal and diagonal boundaries, and the three most distinct bioregions were: West Coast, Central Plains and south-east US.

 The numerical analyses of real world paleobiogeographical data with newly developed “HespDiv” method indeed show a high potential of the approach in objectively defining the hierarchical units of the Bretskyan hierarchy of (paleo)bioregions in sufficiently densely sampled regions and time bins.

                      Presented research is funded by project S-MIP-21-9 “The role of spatial structuring in major transitions in macroevolution”.

How to cite: Daumantas, L. and Spiridonov, A.: “HespDiv” method allows to quantify the dark matter of biosystems, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11519, https://doi.org/10.5194/egusphere-egu23-11519, 2023.

Whether tree-rings faithfully archive the low-frequency variability (LFV) in climate remains debated. In theory, trees are fundamentally limited by being relatively short-lived and therefore unable to capture variations in the climate that are longer than their own lifespans. In addition, near universal practices of “detrending” tree-ring records to remove individualistic age-growth trends place further constraints on the amount of LFV that is maintained in final chronologies. Detrending methods designed to boost LFV may increase low-frequency signals, but how well those patterns reflect true variations in climate as opposed to long growth trends is still unclear. In this study, we first compared the spectral properties of the PAGES North America 2k dataset of temperature-sensitive tree-ring records against long temperature records to determine how much variability is retained in tree-rings after detrending, and how detrending method influences agreement in tree-ring power spectra across space. Then, we compare the spectral properties of tree-rings to the CMIP6 last millennium simulation to validate climate models against long proxy records. This research works to resolve discrepancies between temperature proxies and climate models on long timescales in order to improve our understanding of centennial-scale variability in the Earth’s climate system.

How to cite: McPartland, M., Hébert, R., and Laepple, T.: Do tree-rings match the low-frequency patterns represented in climate models?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12346, https://doi.org/10.5194/egusphere-egu23-12346, 2023.

The evolution of the seasonal rainfall regime and trend in mainland Spain (western Mediterranean basin) in the period 1916-2015 has been analyzed with the new high spatial resolution grid of the MOPREDAS_century (10 km²) database, included in CLICES project.

How to cite: Gonzalez-Hidalgo, J. C., Trullenque-Blanco, V., Peña-Angulo, D., and Beguería, S.: Spatial and temporal variations of the precipitation regime and trend of the last century in mainland Spain, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17369, https://doi.org/10.5194/egusphere-egu23-17369, 2023.

In previous model-data comparisons, the centennial to millennial scale variance of local climate (e.g., SST) reconstructed from proxies was significantly higher than that simulated by climate models. One possible explanation is the lack of long-term feedback mechanisms, e.g. from the representation of changes in ice-sheets in models. Additionally, proxy records are short, and sparse, and the climate signal is significantly modified during the processes of encoding, archiving, and recovery.

Here we introduce new methods to infer the climate variability of the past from proxy data and compare them to new transient model simulations of the last deglaciation. This will allow us to estimate the amplitude of climate variability and to evaluate whether climate models are capable of capturing changes in climate variability between different climate states (e.g. glacial vs. interglacial periods), which is also relevant for the accuracy of future projections. We compare the variability of marine d¹⁸O reconstructed from proxies with that simulated by a state-of-the-art Earth System Model.

From the proxy side, our analysis is based on a new dataset of marine oxygen isotope data from planktonic foraminifera compiled for the PALMOD project. We use new methods to first calculate power-spectra for the LGM, transition and Holocene and then to correct these spectra by fitting a Bayesian model describing the effects of bioturbation and measurement error on the reconstructed climate signal. From the model side we use marine d¹⁸O variability calculated using temperature and salinity from transient model simulations of the last deglaciation, performed within the PALMOD project, that include changes in the ice sheets.

This combination of new data and methods will allow us to investigate the effect of different ice-sheet configurations and physical parametrizations in the model on their ability to characterise long-timescale climate variability and its dependence on climate state.

How to cite: Dolman, A. M., Kapsch, M., Mikolajewicz, U., Jonkers, L., and Laepple, T.: Centennial to millennial climate variability across climate states; proxy reconstructions vs. transient model simulations., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13323, https://doi.org/10.5194/egusphere-egu23-13323, 2023.

Global mean surface air temperature (GSAT) is a key diagnostic for understanding and constraining historical climate variability and change, and for climate policy. Yet, global temperature estimates (1) are usually based on blending sea surface temperatures (SST) with near-surface air temperature over land (LSAT), and (2) contain many missing values due to incomplete coverage in the historical record. While these issues are usually accounted for in model-observation comparisons, elucidating the consistency of LSAT and SST records, and their contribution to GSAT variability and change, remains difficult.

Here, we present a set of new GSAT reconstructions based separately on either the historical LSAT or SST record. The method is based on regularized linear regression models trained on climate model simulations to optimally predict GSAT from the climate model’s LSAT or SST patterns, respectively. We then predict GSAT from the HadSST4 and CRUTEM5 observational data, respectively, for each month from January 1850 up to December 2020.

We demonstrate that the land- or ocean based GSAT estimates show very similar variability and long-term changes, both in the early (1850-1900) as well as in the late record (post-1950). For example, GSAT of the past decade (2011-2020) increased by 1.15°C (LSAT-based) and 1.17°C (SST-based) relative to an early reference period (1850-1900), which is both well within IPCC AR6 estimates.However, the GSAT estimates show pronounced disagreement in the early 20th century (1900 up to around 1930), when the SST-based GSAT estimates appear on average around 0.3°C colder than the LSAT-based estimates. Decadal changes in the LSAT-based estimates are well explained by the multi-model mean of CMIP6 simulations driven with historical forcings, thus implying only a small role of unforced decadal global variability. In contrast, the SST-based estimate highlights pronounced variability during the early 20^th century cold anomaly, which may be related to concerns about instrumental cold biases in SST measurements, but overall reasons for the disagreement remain unclear. Further analysis based on physical reasoning, climate models, and proxy reconstructions, indicates that the ocean data may indeed be implausibly cold.

In conclusion, our methodology and results may help to constrain the magnitude of early 20th century warming, and thus to better understand and attribute decadal climate variability.

How to cite: Sippel, S., Meinshausen, N., Fischer, E., Humphrey, V., Rohde, R. A., de Vries, I., and Knutti, R.: New Land- vs. Ocean based Global Mean Temperature Reconstructions reveal high consistency except for early 20th Century Ocean Cold Anomaly, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11039, https://doi.org/10.5194/egusphere-egu23-11039, 2023.