dataesr/scientific-paragraphs-categorization huggingface dataset:
Vincens (CEREGE, France) for sharing their pollen data (Tilla and Mbalang, respectively). All pollen records are archived in the African Pollen Database (APD). T. , Ramesh, R. , Rojas, M. , Shao, X. and Timmermann, A. , 2013, Information from paleoclimate archives. In Climate Change 2013: the Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, edited by Stocker, T. F. , Qin, D. , Plattner, G. -K. , Tignor, M. , Allen, S. K. , Boschung, J. , Nauels, A. , Xia, Y. , Bex, V. and Midgley, P. M. pp. 383-464 (Cambridge University Press). Mazier, F. , Gaillard, M. J. , Kuneš, P. ,  Sugita, S. , Trondman, A. K. and Broström, A. , 2012  Radiocarbon dating indicates that the base on the core is close to 7000 years old.
General observations The results of the pollen analysis are given in Figure  4. Assigned names have been amended to follow the format of the African Pollen Database  (Vincens et al. 2007 ). The pollen taxa have been grouped in 'ecological groups'. However, as pollen determination has often only been possible to generic or even family level, this is problematic when a recorded pollen type could have originated from more than one life form or vegetation type. The groupings in Figure  4 , therefore, represent the life forms and vegetation types from which the recorded pollen types are most probably derived, although this is an over-simplification. In making this zonation, reference has been made, in particular, to  Hutchinson and Dalziel (1954-1968) ,  Hall and Swaine (1981) ,  Letouzey (1968 Letouzey ( , 1979)) ,  Nielson (1965)  and  Sowunmi (1981).
New methods and resources The CREST (Climate REconstruction SofTware) method developed by  Chevalier et al. (2014)  has been very successful in producing quantitative climate reconstructions for southern Africa using contemporary climate data, modern plant distributions and fossil pollen records  (Chase et al. 2015a; Chase et al. 2015b; Chevalier and Chase 2015; Chase et al. 2017; Chevalier et al. 2021; Cordova et al. 2017; Lim et al. 2016). A major advantage of this method is that a large modern pollen database (which does not currently exist for the CFR) is not required. The steep environmental gradients and coastal settings of many of the CFR pollen records have proven to introduce a great degree of complexity to the application of CREST within this region. However, there certainly still is scope for its application particularly with the addition of a new resource: A 'by-product' of the CREST method has given rise to the 'Atlas of southern African pollen taxa: Distributions and Climatic Affinities'  (Chevalier et al.
this volume) which will greatly improve, refine and standardize qualitative interpretations of fossil pollen data as well as quantitative reconstructions (such as CREST). This reference atlas includes a series of diagnostic tools and results based on statistical analyses of modern distributions of common southernAfrican pollen taxa in relation to key climate variables. This new resource reduces the subjectivity often inherent in more qualitative interpretations and presents more accurate determination of absolute and relative climate sensitivities of southern African pollen types, including a large proportion of CFR taxa. The recent digitization of CFR pollen reference material (originally from the Palaeoecological Laboratory in the Department of Environmental and Geographical Science, University of Cape Town) and the establishment of a new open access, searchable electronic database (http://pollen.
mandela. ac. za) represents a new primary palynological resource. While the resurrection of the African Pollen Database (APD,  Vincens et al. 2007 ) and its integration into the Neotoma Palaeoecology Database  (Goring et al. 2015) , will ensure that previously published and new pollen datasets are archived within an open access online platform  (Ivory et al. 2020). If the majority of fossil pollen records for the CFR were included in the new APD -Neotoma database, new forms of spatiotemporal analyses could be conducted which would provide greater insight into ecosystem-climate linkages across the region.
2007). There are three main approaches to the reconstruction of past land cover from pollen data: biomisation, modern analogue approaches and modelling the pollen-vegetation relationship. Biomisation approaches convert pollen data into plant functional types, then use ratios of these types to identify the biomes present in past landscapes  (Jolly et al. 1998; Vincens et al. 2006) , combining sites to map past land cover at biome level across regions and continents. Modern analogue approaches take spatially extensive datasets of modern pollen assemblages and associated environmental parameters (e. g. climate factors such as precipitation or mean annual temperature, or indices of landcover), develop transfer functions or other mathematical models such as the CREST model (e. g. Chevalier et al.
Extended R-value analysis (ERV) Extended R-value analysis is an iterative computational approach to estimating values of relative pollen productivity from a bivariate dataset of modern pollen counts and distance-weighted vegetation abundance  (Parsons and Prentice 1981; Prentice and Parsons 1983). By applying this analysis to vegetation data surveyed out to different distances from the sample point, it is possible to assess the spatial sensitivity of the pollen signal in the samples (by identifying the Relevant Source Area of Pollen -Sugita 1994), which provide the best estimates of relative pollen productivity (RPP -amount of pollen produced per unit vegetation, expressed as a ratio relative to a reference taxon) for the studied landscapes and can inform the spatial interpretation of past land cover around pollen sites with similar characteristics.
2018; Marchant and Taylor 2000; Schüler et al. 2014) , thereby limiting palaeoecological inferences and attempts to model vegetation from pollen data. Southern Africa has an established tradition of palynological research, dating back to the pioneering efforts of  van Zinderen Bakker (1950 , 1951). Early palynologists often incorporated a few surface pollen spectra to support fossil pollen records (e. g. Cooremans 1989; Scott 1982a Scott , b, 1989;; Scott and Cooremans 1992; Scott et al. 1992) , however, relatively few dedicated studies, particularly those with a temporal component, exist  (Hill 1995). A recent modelling synthesis of modern pollen data from southern Africa pulled together a dataset of mostly surface soil samples DOI 10. 1201/9781003162766-17 from 211 sites across the subregion  (Sobol et al.
These comparisons allow palaeoecologists to determine which plants produce lots of pollen grains relative to their vegetational abundance and which produce very little. Modern pollen datasets are increasingly being used to calibrate models of pollen dispersal and deposition, allowing for more quantitatively rigorous reconstructions of past vegetation to be developed  (Fang et al. 2019). In temperate regions, there has been an abundance of studies conducted on modern pollen rain  (Davis et al. 2013) , and these results have been used to calibrate models of pollen dispersal and deposition  (Bunting and Middleton 2005; Jackson and Lyford 1999; Theuerkauf et al. 2016 ). These models have allowed increasing accuracy and precision of vegetation reconstructions, but often rely on extensive datasets, which are relatively rare in the tropics  (Bonnefille et al.
Recently, 20 modern pollen (and phytolith) samples from springs in Awash Valley have been published  (Barboni et al. 2019)  which allowed records from fossil springs to be interpreted. These spring environments are thought to be important environments for early hominins, as constant supplies of water in otherwise fluctuating or arid landscapes, therefore playing an important role in early hominin evolution and dispersal. A large number of modern pollen samples from Ethiopia (with fewer samples from Kenya and Burundi) were included in studies that aimed to develop transfer functions to reconstruct rainfall  (Bonnefille et al. 1992; Roeland et al. 1988 ) and temperature in fossil records. It was found that it is possible to reconstruct modern temperatures and precipitation with a high degree of accuracy based on the large and geographically widespread datasets used in the analyses.
The presence of Ericaceae-dominated montane shrub grasslands and the forest formations of the northern and eastern parts of the island were recorded. Along these, ecosystems such as riparian woodlands on the lakeshores, patches of montane were also represented as the case of the sample collected at Ankazominady in the central highlands. These findings enabled interpretations of palaeoecological work and established at least a qualitative distinction between Malagasy paleoenvironments in the region. However, Burney suggested the need for larger modern pollen datasets and the inclusion of more phytogeographic information combined with multivariate statistical methods for better interpretations. Straka (1991)  published 89 samples from mosses and surface sediments within which 60 samples were from Madagascar.
The technique has been developed extensively over the last decade and is becoming a valuable tool for investigations of patterns of and controls on land cover change, especially in the northern temperate zone (e. g. Marquer 2017; Li et al. 2020). Challenges in extending the pdd approach (and the modern analogue approach) to the tropics are two-fold-collecting calibration datasets of modern pollen and associated vegetation data, and the development of appropriate pollen dispersal models. Identifying appropriate trapping techniques in tropical ecosystems can be difficult; many ecosystems lack natural pollen traps such as moss polsters, and some ecosystems are too arid or fire-impacted to allow multi-year trap placement and recovery, which has been shown to be advantageous in tropical systems  (Haselhorst et al.
g. Harrison et al. (2020) ), adding a long term perspective critical to meet socioecological challenges such as planning for climate change adaptation and mitigation. This review can support the use of pdd modelling in African palynology by showing the range of data available across the continent. Existing pollen datasets can be identified in locations where it may be possible to extract suitable vegetation data from remote sensing and data collected for other purposes, and achieve initial model calibration for major habitats. We also hope to alert colleagues to the potential of modern pollen samples, and therefore encourage study design which can be used for model testing and calibration as well as for the analyst's primary purpose.
COMPILATION OF THE RECORDS In this study, we use all the available marine pollen records from Africa with an appropriate age model stored in the African Pollen Database (APD) and Pangaea as well as those delivered by authors upon request. Out of 95 marine sites illustrated in Figure  1 , only 60 pollen records have the potential to document the vegetation response to climate variability and, therefore, have been used in this paper (Supporting Online Material [SOM] Appendix Table  1 ). All of the radiocarbon-dated records considered here have age models in calendar years (cal kyr BP) after conversion of 14 C dates to calendar age according to  Stuiver et al. (2020). The age models were directly retrieved from the published articles or from the APD (i. e. based on linear interpolation between the dated samples) taking into account the marine reservoir age of 400 years, which reflects the present-day global average  (Hughen et al.
2004 ). Age models beyond the limit of radiocarbon dating were based on the marine oxygen isotope stratigraphy. Selected sites with sufficient temporal resolution were used to illustrate the different patterns of the vegetation response to major climatic events in a centennial-, millennial-and orbital-time scale (Figures  2, 3  and 4 ). The whole dataset was then used to map tree pollen distribution in marine sediments off African shores at a continental scale throughout different climate cycles (Figure  5 ). Tree pollen types include trees, shrubs, palms and lianas. Percentages are calculated against a sum of total pollen excluding those of aquatics (including Cyperaceae) and Pinus (SOM Appendix Table  2 ).
Figure3. ERV analysis output for RSAP estimations. Illustrated are likelihood function score graphs for pollen-vegetation datasets run with Sutton's taxon specific distance-weighting using ERV model 1. RSAP is visually estimated from the graphs where the curve tends to an asymptote. While the maximum vegetation survey distance was 5000 m, a logarithmic scale was used to 1000 m from sample points as an asymptote had been reached by this distance.
ACKNOWLEDGEMENTS This work is an " ACCEDE" Belmont Forum contribution  ( 18 BELM 0001 05 ). Thanks are due to the  Institut de Recherche pour le Développement (IRD)  and the  UCAD Geological Department (Dakar, Senegal)  for logistic support in the field and authorizations and to the  ECLAIRS International Laboratory (Dakar)  and the  LOCEAN Laboratory (Paris)  for funding. KL and AML are funded by  CNRS, France.
ACKNOWLEDGEMENTS This work contributes to the  ACCEDE ANR Belmont Forum  project (( 18 BELM 0001 05 ). Thanks are due to  M. J. Gaillard  ( Kalmar University, Sweden ) for constructive comments on the manuscript and the African Pollen Database for data access. AML and KL are funded by  CNRS , LD by the  University of Bremen  and IB by the  BMF  grant  PMARS2015-100.
ACKNOWLEDGEMENTS Our sincere gratitude goes to the following institutions,  National Museums of Kenya (NMK) ,  University of Cape Town ,  Smithsonian Institution , and  University of Calgary. Support from the  Peter Buck Fund for Human Origins Research (Smithsonian)  is much appreciated acknowledged. We also thank  Alan Deino  for his long-term collaboration on the geological dates discussed in this paper;  Jennifer Clark  for her assistance in all the logistics that involved the  Smithsonian Institution  and for assisting with the figures;  Drs. Veronica Muiruri  and  Stephen Rucina  for the technical provisions during analyses at the  Palynology and Paleobotany lab, NMK.
ACKNOWLEDGEMENTS We thank  Stephen Rucina ,  Veronica Muiruri ,  Rahab Kinyanjui  and  Rebecca Muriuki  from the  National Museums of Kenya, Palaeobotany and Palynology Section  for field and laboratory support;  Joseph Mutua  and  Nicholas Gakuu  for fieldwork logistics; and the  British Institute in Eastern Africa (Nairobi)  for their continued support. We thank  William Gosling ,  Anne-Marie Lezine  and  Louis Scott  for their organisation of this special issue. This study contributes to the African Pollen Database (APD),  Neotoma Paleoecology Database , and the  PAGES supported Global Paleofire Working Group  ( GPWG2 ) and  PAGES-LandCover6k. Past Global Changes (PAGES)  is funded by the  Swiss Academy of Sciences and Chinese Academy of Sciences  and supported in-kind by the  University of Bern , Switzerland.
ENG and CCM were supported by a  European   Commission Marie Skłodowska-Curie Initial Training Network grant  to RM and coordinated by  Paul Lane through Uppsala University  (FP7-PEOPLE-2013-ITN project number  606879 ). 210Pb and C/N data presented in this paper was supported by  NERC  Radiocarbon Allocation 1681. 1012 or funded by the  Natural Environment Research Council NERC  standard grant number  NE/I012915/1  to  Dan Charman  at  University of Exeter, UK , and we thank  Angela Gallego-Sala  and the  Millipeat  Project. This research formed part of the PhD dissertation of  EG, University of York. In memory of our friends and colleagues,  Richard Payne  and  Eric Grimm.
ACKNOWLEDGMENTS This work contributes to the  ACCEDE ANR-NSF Belmont Forum project  ( 18 BELM 0001 05  and  NSF-1929563 ) as well as  NSF-CNH 1617185. Thanks are due to the African Pollen Database for data access. SJI is funded by  Penn State University , AML is funded by  CNRS, MD  is funded by the  DFG priority program SPP Entangled Africa.
ACKNOWLEDGEMENTS This research was supported by the  National Research Agency (ANR) ,  France , through the  C3A  ( ANR-09-PEXT-001 ) and  VULPES  ( ANR-15-MASC-0003 ) projects and by the  Labex L-IPSL. We gratefully acknowledge funds from the  CNRS  ( A. -M. Lézine ), and  Linnaeus University (Faculty of Health and Life Sciences, Kalmar, Sweden)  and the  Swedish Strategical Research Area 'ModElling the Regional and Global Ecosystem ' (MERGE; http://www. merge. lu. se/) ( M. -J. Gaillard ,  E. Githumbi ,  F. Li ). This study is also a contribution to the  Past Global Change (PAGES)  project and its working group LandCover 6k (http://pastglobalchanges. org/landcover6k), which in turn received support from the  Swiss National Science Foundation , the  Swiss Academy of Sciences , the  US National Science Foundation , and the  Chinese Academy of Sciences.
ACKNOWLEDGEMENTS This work was carried out as an  MSc  project in the early 1980's at the  Department of Geography, University of Hull  under the guidance of the late  John R. Flenley  and at  Duke University , assisted by the late  Daniel A. Livingstone. This paper is dedicated to the fond memory of both JRF and DAL whose support and encouragement made this study possible. Partial funding was received from The  Nuffield Foundation. Margaret Adebisi Sowunmi  ( University of Ibadan ) provided assistance with some pollen identification and  Miranda Awo  ( University of Buea ) provided upto-date information on the vegetation, plant-pollen relationships and limnology of the study region. Ron Hatfield  of  Beta Analytic Inc. assisted with calibration of radiocarbon ages. Figures 2 and3 were re-drawn by Alison Davies of The Mapping Company, UK, from originals drawn at  Hull University, Department of Geography.
ACKNOWLEDGEMENTS TRH was funded by the  Foundation for Research and Development and Rhodes University. Brice Gijsbertsen  professionally drafted Figure 1. The staff of  Cathedral Peak Forestry and Research Station  are thanked for their hospitality, and for allowing the opportunity to work in such tranquil surroundings. Thank you to Colin and  Terry Everson , and  Martin Hill  for assisting with fieldwork. Andrew Steele  assisted with data entry. Elodie Heyns-Veale  kindly assisted with the multivariate analysis. We thank  Henry Lamb  and one anonymous reviewer for constructive feedback on the manuscript.
ACKNOWLEDGEMENT We would like to thank the editor and the reviewers for providing helpful feedback to improve the manuscript. We would also like to thank the team in Madagascar that helped with the field work and  Tsilavo Razafimanantsoa  for helping with the map. This project has been funded as part of the  Faculty PhD fellowship  ( University of Cape Town ,  R. E. ) 2015-2018  and the  Applied Centre for Climate and Earth Systems Science  ( ACCESS NRF UID 98018 , R. E. ) project, the  UCT University Research Committee  accredited (URC) from the  University of Cape Town [URC ,  2019-2020 ] and  SASSCAL (Southern African Science Service Centre for Climate Change and Adaptive Land Management ) [466418 c/c  BIO1056 , 2020].
ACKNOWLEDGEMENTS We would like to thank  Dr. Anne-Marie Lézine  and  Prof. Henry Hooghiemstra  for kindly sharing papers and information that greatly helped this review. Prof. Christelle Hély  and an anonymous reviewer also provided helpful and detailed comments that significantly improved the work, for which we are extremely grateful. ACMJ acknowledges funding from the  NRF African Origins Platform  ( 117666 ). SM fromthe  NRF Competitive Programme for Rated Researchers  ( 118538 ). ER acknowledges The  Southern African Science Service Centre for Climate Change and Adaptive Land Management  (SASSCAL, 466418 c/c  BIO1056 ) and the  University Research Committee  accredited (URC) from the  University of Cape Town  ( 2020 ). DH acknowledges funding by  CongoPeat , a  NERC Large Grant  ( NE/R016860/1 ) to  Simon L.
ACKNOWLEDGEMENTS The authors wish to express their gratitude to all African Pollen Database (APD) contributors and colleagues who made their data available for this study and for the excellent discussions during the APD meeting in Bondy. We thank  Henry Hooghiemstra  and  William D. Gosling  for their constructive comments on the manuscript. IB, HR, AB are funded by the  German Federal Ministry of Education and Research (BMBF) , through the  PMARS III grant  ( PMARS2015-100 )". LD by the  University of Bremen , and AML by  CNRS.
ACKNOWLEDGEMENTS We would like to thank all the authors of the original publications which we review here for publishing their studies and making their data available either through open access databases or directly following corresponance. We thank  Alayne Street-Perrott  ( Swansea University, UK ) and  Anne-Marie Lézine  ( CNRS, France ) for their thorough evaluation and feedback on our manuscript, and the PoA editorial team for the opportunity to contribute to this volume.
, 1986, Pollen percentages, tree abundances and the Fagerlind effect. Journal of Quaternary Science, 1, pp. 35-43, 10. 1002/jqs. 3390010105. : Mboandong is a small crater lake situated approximately 30 km to the north of Mount Cameroon. A core 13 m in length was collected from the lake centre in December 1981 with the objective of studying Holocene vegetation change in the lowlands of West Cameroon. , Testing the effect of site selection and parameter setting on REVEALS-model estimates of plant abundance using the Czech Quaternary Palynological Database. Review of Palaeobotany and Palynology, 187, pp. 38-49, 10. 1016/j. revpalbo. 2012. 07. 017. Keith Richards 1 Navya R. , 2020, Pollen based estimates of Holocene vegetation in southern India: An LRA (Land-cover Reconstruction Algorithm) approach", PhD Thesis, Pondicherry University, Puducherry, KrA Stratigraphic, Deganwy, Conwy, North Wales, United Kingdom India, pp.
Yet, this is crucial to know because very likely the chemical composition and fate of the future planetary systems depend on the chemical class to which the original protostar belonged. The aim of this paper is to introduce the ALMA (Atacama Large Millimeter/submillimeter Array) Large Program (LP) FAUST (Fifty AU STudy of the chemistry in the disk/envelope system of Solar-like protostars; http://faust-alma. riken. jp), focused on astrochemistry of Class 0/I sources imaged at the Solar System spatial scale.
The high-angular scale of 50 au will be reached using the 12-m antenna ALMA array in different configurations. Furthermore, given the goal to sample also the molecular envelope, Atacama Compact Array (ACA/Morita Array) observations of 7m antennas will be also performed. By combining all the visibility data obtained using both the 12m and the 7m antennas array, FAUST will be able to follow the physical and chemical changes from the large-scale envelope (∼ 2000 au) to the inner disk/jet system. For each frequency setting, we allocate one continuum setting to measure the dust Spectral Energy Distribution (SED) from 3 mm to 1 mm. The frequency resolution is set to 0. 2 km s -1 , i. e. the sound speed at 10 K.
First FAUST results and perspectives The analysis of the FAUST data is in progress. However, some instructive results have been already obtained. The data were reduced by using a modified version of the ALMA calibration pipeline and an additional in-house calibration routine (G. Moellenbrock et al. 2021, in preparation)  to correct for the system temperature and spectral line data normalization. Figure  2  reports an example of the zoo of FAUST spectra observed in a portion of the frequency Setup 2 (see Table  1 ) towards the protostellar coordinates. The spectra have been obtained merging ACA data with those at high-spatial resolution. The line identification and the discussion of the chemical content is out of the focus of the present paper; the goal of the spectra sketched in Fig. 2  is to enlight a chemical differentiation, indicating the source sample is not biased by some selection criterium.