dataesr/scientific-paragraphs-categorization huggingface dataset:
This pattern could be the result of a non-linear relation of cocoa suitability with climate variables, suggesting that a moderate increase will be positive but that it will turn into negative under the more extreme scenario. This result rejects our basic initial hypothesis and contradicts previous studies carried out in West Africa where they forecasted a considerable reduction of suitability in the region  [4] [5] [6]. The differences of habitat suitability patterns may be related to the use of different datasets and algorithms. Nevertheless, some of these ndings are in line with those of Black et al. (2021), who found that in the regions where cocoa is currently grown in Ghana, Côte d'Ivoire and Togo, the net primary productivity (NPP) is projected either to stay the same or to increase slightly.
Here, we used a comprehensive consensus approach from the global distribution of cocoa which is the widely accepted methodology to characterize the current potential distribution of species  22, 23. However, previous studies only considered data from Côte d'Ivoire and Ghana or constructed distribution maps based on expert knowledge  5. This restricted dataset limits the ability of the model to predict the suitability of the species as it only considers a narrow climate variability. In addition, different from previous studies, we used the latest climate projections from the new CMIP6 models. The projected increase in suitability occurs mostly in the central part of Côte d'Ivoire and south-eastern Nigeria but under marginal suitable levels (i. e. , < 60%) which might not be su cient to guarantee pro table cocoa production.
Occurrence dataset. We obtained for all 45 species, a total of 33,895 occurrence points from the Global Biodiversity Information Facility (GBIF) (https://www. gbif. org) at global scale (list of all downloads used in supplementary material Table  S1 ). Unsuitable presence locations points were identi ed and deleted in a step-by-step procedure, according to the following criteria: records i) with no geographic information or with incomplete coordinates; ii) with clear errors such as locations in the ocean and mismatches between administrative data and coordinates; iii) collected before 1969 to meet the current baseline climate used; iv) in marginal climates (e. g. , botanical gardens in temperate climate) within the last 10% of the climatic gradient distribution and; v) "fossil" records or from unknown sources.
We also reduced the possible effects of sampling bias and spatial autocorrelation keeping only one record per species per 2. 5 arc-min grid (to overlap with environmental information). Finally, we selected those species with n > 60 presence locations points. The nal dataset included 14,368 occurrences for 38 shade tree species and 401 locations points for cocoa. The algorithms used in this study require absence data for calibration and validation of the model, but reliable absence information is rarely available. Thus, we generated 1000 pseudoabsences per species randomly drawn from an area less than 500 km from the occurrence points per species. This buffer area was a good compromise to identify distinct environmental conditions without over tting results  37. Environmental data compilation and pre-processing.
Soil data was extracted from SoilGrids database  39  (https://soilgrids. org), which provides maps for ten different soil properties at six different depths. The download of selected SoilGrids layers (Table  1 ) was performed with Google Earth Engine (GEE) using the rgee package  40. In this work, we used the 5 km resolution les averaged for layers from 30 cm to 1 m depth as it represents most relevant horizon for trees independent of soil management. To be conservative, we assumed that edaphic variables remain constant under future scenarios  41. The environmental dataset was reduced by analysis of collinearity using the Variance In ation Factor (VIF). The predictor variables with VIF > 8 were removed  42. Then, a correlation matrix using Pearson's correlation coe cient was calculated and variables with (r > 0.
The AUC and TSS values of the selected SDM models and the ensemble model are shown in supplementary material Table  S3. The relative importance (%) of each environmental variable was estimated per species according to the best algorithm. We also tested whether the accumulated relative importance between climatic and edaphic variables varied across the main use and the origin of the species using post-hoc Tukey tests in a linear regression using the R package multcomp  47. All data processing and model development was carried out using the R package BiodiversityR based on the work ow by  12. Model projections and outputs. As a study area, we have delimited a 2. 904. 160 km 2 band of land covering the total area of the main cocoa-producing countries in West Africa (Côte d'Ivoire, Ghana, Nigeria, Cameroon, Sierra Leone, Liberia, Togo, Benin, Guinea and Guinea-Bissau).
Climate information was extracted from the WorldClim-Global Climate Database 38 (https://worldclim. org/),reporting gridded mean climate values from a baseline period of 1970-2000. The dataset was downloaded globally at 2. 5 arc-min spatial resolution (~ 5x5 km at the equator). The dataset considered 19 climate variables commonly used in biogeographical studies. Outputs from the new circulation models of the Coupled Model Inter-Comparison Project Phase (CMIP6) were used to assess projected changes in future climate. Downscaled monthly future climate data from CMIP6 is available for nine global climate models, and four SharedSocio-economic Pathways (SSPs). To provide plausible future scenarios for management, we selected two contrasting SSPs scenarios (i. e. , SSP126 and SSP585), and the two rst periods (i.
Acknowledgments This research is of the  Forecast Scenarios for Cocoa Agroforestry (CocoAgroForecast)  project and is partially based on the work ow by 12 on climate risk and vulnerability of cocoa agroforestry systems in Mesoamerica. Pablo  González Moreno  was supported by a  "Juan de la Cierva-Incorporación " contract (MINECO,  IJCI-2017-31733 ) and  Plan Propio UCO 2020.
9m, r ). The salinity biases in different depth ranges altered in such a manner that the overall upper ocean stratification in the Amerasian Basin is enhanced, resulting in shallower MLD than in the low-resolution configuration (Fig. 12h ). Similarly, the decrease in the MLD in the high-resolution FSU-HYCOM model (Fig. 12i ) can be partially explained by the amplified fresh bias at surface (comparing Fig. 9i ,s with Fig. 9d, n ). Additionally, we computed the MLD in March using the density threshold of 0. 03 kgm -3 and made the comparison with the MIMOC MLD dataset  (Schmidtko et al. , 2013) , which also used this threshold. This comparison yields similar findings to those described above (Figure  S3 ).
Acknowledgements. We thank the present and past members of the  CLIVAR Ocean Model Development Panel  who have designed and supported the  Ocean Model Intercomparison Project (OMIP). QW is supported by the  Helmholtz Climate Initiative REKLIM (Regional Climate Change and Human)  and the  EPICA project in the research theme  "MARE: N -Polarforschung/MOSAiC " funded by the  German Federal Ministry for Education and Research  with funding no. 03F0889A. QS is supported by the  National Natural Science Foundation of China  (grant no. 42276253 ), the  Shandong Provincial Natural Science Foundation  (grant no. ZR2022JQ17 ), and the  Taishan Scholars Program  (grant no. tsqn202211264 ). AK is supported by  ARC  grants  LP200100406. BFK is supported by the  SASIP  project of the  Schmidt Futures Foundation.
Code and data availability. The following OMIP model output, published on the Earth System Grid Federation, has been used: ACCESS-MOM (ACCESS-OM2)  (Holmes et al. , 2021) , CMCC-NEMO (CMCC-CM2-SR5)  (Fogli et al. , 2020) , IAP-LICOM (FGOALS-f3-H and FGOALS-f3-L)  (Lin, 2019 (Lin, , 2020)). The 1/10°ACCESS-MOM data is available from http://dx. doi. org/10. 25914/608097cb3433f. The model data used to produce the figures and the corresponding analysis scripts are archived at http://dx. doi. org/10. 5281/zenodo. 8046638.
Data was retrieved for allele data from databases, article supplements, and direct author communications. The dataset, version 1. 0. 2, encompasses data from 52 species, with 46 species for the Clock gene and 43 for the Adcyap1 gene. This dataset, featuring data from over 8000 birds, constitutes the most extensive cross-species collection for these candidate genes, used in studies investigating gene polymorphisms and seasonal bird migration.
It is therefore no surprise that many candidate gene studies have explored variation within the network of genes of the circadian clock. Several associated candidate genes have been suggested, with length polymorphisms within short repeats of the Clock and Adcyap1 genes being the focus of many studies  [31] [32] [33]. To clarify the role of these genes in migratory phenotypes, a systematic review (Fig. 1 ) was conducted to identify, synthesise, and provide a reappraisal of the available evidence  34. Structured searches of the literature with an optimised Boolean search string were done in five scientific databases. Search results were exported in formats compatible with citation network analysis software  35. After duplicate entries were removed, citation network analyses were used for the automated screening of database results to identify the central literature on the topic.
Publications identified from the citation network analyses were subjected to manual screening of the title, abstract, and key words to assess the potential eligibility for inclusion in the review. The final list of most eligible publications was sought for full text retrieval. A total of 66 studies were included in the final review of which 34 were candidate gene studies and 32 were other, migration-related, studies. These included latitude/longitude/ spatial analyses, timing of migration, and timing of egg laying/breeding. Most of the studies using a candidate gene approach were used for data retrieval. For these studies, datasets were retrieved as either diploid allele data of individuals or allele frequencies. Data sources included the main text of articles, supplementary materials, databases such as Dryad (https://datadryad.
org/) or Figshare (https://figshare. com/), data extraction, or data received directly from authors. Unpublished data for an additional 12 species were also included. The dataset included individual level allele data from 52 species of which data was available for 46 species for the Clock gene and 43 species for the Adcyap1 gene. This dataset represents the largest collection of cross species allele data for two candidate genes used to test a putative association between clock gene polymorphisms and divergent migration in birds, which enables the testing for patterns of inheritance, evolutionary selection, relation to divergence times, and associations across a globally distributed dataset. This data descriptor summarises both the methodology used to screen the literature as well as to compile the data concisely and presents the resulting data used in prior analyses in an easy-to-understand format.
At present, none of the scientific databases that collect genetic variation data is suitable for the deposit of this specific type Fig. 4  Geographic distribution of candidate gene studies included in the final review dataset (N = 34) based on sampling locations. Related migration studies (N = 32), such as transcriptomic or epigenetic studies, were excluded. The density gradient plots the number of studies per country ranging from one study (green) to more than eight studies (red); countries in white are data deficient. The overall plot indicates that most studies emanated from sampling locations in Europe and North America, with only a small number of studies including sampling from parts of Africa and South America. of data. The barcode of life data system (BOLD, https://boldsystems. org/), which does accept length polymorphism data from microsatellite markers, currently only accepts data for markers used in barcoding or population assignment experiments and does not specifically store data for markers used in behavioural or phenotype associated studies.
The European variant archive (EVA, https://www. ebi. ac. uk/eva/), which also accepts variant data that includes length polymorphisms, currently only accepts data for species with reference genomes, which is still unavailable for most avian species. To overcome this, we have endeavoured to create a central compilation of the available data in two standard formats which is archived in parallel to this data descriptor; with an additional online version on GitHub 36 (https://github. com/LSLeClercq/AvianClocksData) that will be maintained and updated over time as more data is made available. This may greatly facilitate the reuse of the data where it may be applicable to other forms of analyses within migration genetics and beyond.
Methods Literature search and automated screening. Literature was searched using systematic review methods, in line with PRISMA Ecology and Evolution guidelines  37  , to identify and synthesize relevant sources. The overall approach is depicted in the PRISMA statement  38  in Fig. 1  that was supplemented with further information on the data retrieval and screening process. Literature was searched between January and September of 2022 on five databases: Scopus (N = 52, www. scopus. com), ScienceDirect (N = 1814, www. sciencedirect. com), Web of Science (N = 140, https://clarivate. com/), PubMed (N = 157, https://pubmed. ncbi. nlm. nih. gov/), and Dimensions (N = 2746, www. dimensions. ai). Databases were searched using an optimized Boolean search string derived from the PICO terms for the aim and objectives of the review.
The final search string was as follows: ("Birds" OR "Avian") AND ("Clock genes" OR "Clock" OR "Adcyap1" OR "Candidate gene") AND ("Migration" OR "Flying"). As needed, this was complemented by ancillary 'free term' searches based on citations in articles or to include other relevant aspects such as "Breeding", "Moult", "Genomics", "Transcriptomics" or "Photoperiod". For the Scopus and Dimensions database searches, the results were exported in the comma separated value (CSV) format, while the results from the ScienceDirect, Web of Science, and PubMed database search were exported in the research information systems (RIS) format. Automated screening for inclusion was done through citation network analyses. For the Scopus database, the results were merged and reformatted with the R package 'Scopus2CitNet 0.
1. 0. 0' (https://github. com/ MichaelBoireau/Scopus2CitNet) in RStudio 1. 4. 1106  39  , running R 4. 0. 5  40. The results were subsequently visualized by year in CitNetExplorer 1. 0. 0. , keeping only those papers that overlapped in terms of references cited and the largest connected set (Fig. 2a ). The results from the search on the Dimensions and ScienceDirect databases were visualized in VOSviewer 1. 6. 16  35  by group as well as by year, keeping only those papers that are connected by citations and reference lists (Fig. 2b ). The size of bubbles corresponds to citations and the number of cross-links between studies. Manual title-abstract screening and full text retrieval. Sources identified from the citation networks were imported (citation and abstract) into Mendeley citation manager (www.
The final set of studies that passed preliminary screening were sought during full text retrieval and added to the imported reference if it wasn't already included. A total of 66 studies were included in the final review of which 34 were candidate gene studies and 32 were other, migration related, studies using genetic methods. Some basic scientometric assessments of the final set of studies, including the plotting of publications per year (Fig. 3 ) as well as the geographic distribution (Fig. 4 ) of studies, was conducted using ABCal version 1. 0. 2  41  (https://github. com/LSLeClercq/ABCal).
Published datasets. A total of 34 studies were identified that used a candidate gene approach for which data retrieval was done. Data was retrieved from either the main text, supplementary material of the article, online data repositories such as Dryad  [42] [43] [44] [45] [46] [47] [48] [49]  and Figshare  50  , or additional data received directly from authors. Data types varied from allele frequencies to individual level diploid allele data. Allele data for the Barn swallow  51  was retrieved from the text while data for the Yellow-legged gull  52  was extracted from images using WebPlotDigitizer version 4. 6  53. Allele data was generally derived from a single source with the exception of the European pied flycatcher  44, 49  and Willow warbler  [54] [55] [56]. The species, data sources, and data types are summarized in Table  1  along with the sampling location and sample sizes.
Frequency data was available for most published studies, with the exception of the bluebird species  18  , and those species for which allele data was unavailable are summarised in Table  2. This includes species for which only frequency data was reported, species for which a non-clock gene approach was used, and studies for which only data summaries without frequencies were reported. Unpublished datasets. This study included unpublished data for twelve species in total, summarised in Table  3. The six North American species were sampled at Long Point Old Cut, Ontario, Canada Shearwaters were sampled from several locations in Europe including France and Portugal while several species were sampled from islands such as Iceland, Cape Verde, and territories of the United Kingdom such as Gough Island.
Data Records The data collated during the systematic review and meta-analysis were made available to via the Zenodo repository at the time of publication. Additional inclusion and exclusion criteria were applied and a final set of 40 species (indicated by asterisk in Tables  1, 3 ) were included in the comparative analyses using mantel and phylogenetic generalised least squares methods to test for an association between migratory phenotypes and candidate gene genotypes  34, 57. This data are available on Zenodo  57  , and includes a workbook with the allele data as well as a results workbook with various population genetics measures including allele frequencies, Homozygosity (H o ), Heterozygosity (H e ), Hardy-Weinberg equilibrium  58, 59  , and Ewens-Watterson 60 results. The complete dataset was reformatted for distribution with this data descriptor and is available from two sources, from the Figshare 61 depository, as submitted with this article, and from a maintained repository with version histories on GitHub  36.
Data (version 1. 0. 2) are available as a spreadsheet workbook, labelled "Avian Clock Gene Dataset" with multiple sheets. The first sheet of the workbook, labelled "Index", contains the table of contents which has several columns (Table  4 ) that list species by common names, indicates data availability for Clock and Adcyap1, and total sample size (N). Furthermore, the taxonomic classifications including genus, species, family, superfamily, parvorder, and order are also given. The species codes are hyperlinked to the allele data for individual species, contained in separate sheets within the same workbook. Individual sheets for species contain several columns including the species name, sample ID, and diploid alleles for Clock and/or Adcyap1 genes. Alleles are expressed as the number of polyglutamine repeats (Q N ) for Clock while the Adcyap1 alleles represent the amplified fragment length in base pairs (bp).
Acknowledgements Open access provided by the library of  University of the Free State  (Grant number:  13560591 ). The authors would like to thank  Chris Guglielmo ,  Yolanda Morbey , and  Ivan Maggini  for support with field data collection at  Long Point Bird Observatory (Canada ),  Staffan Bensch  for field data collection in both Sweden and Kazakhstan, and  Andrea Galimberti ,  Cristina Possenti ,  Fernando Spina  and the late  Nicola Saino  for support with genetic analyses and field data collection in Ventotene Island (Italy). Images were created/edited in BioRender. com. This work is based on the research supported wholly/in part by the  National Research Foundation of South Africa  (Grant Number:  112062 ). The study received partial financial support from the  PRIN 2017  funding scheme (grant number  20178T2PSW  to Diego Rubolini), from the  ICREA Academia  award (to  Jacob González-Solís ), and from the  Ministerio de Ciencia e Innovación, Agencia Estatal de Investigación, España  ( PID2021-125792NB-I00  to  Marta Riutort ).
Methods In the model, annual fish individuals can find themselves in different pond compartments and environments (Figure  one ). The state of the pond is described by the amount of water it contains. A pond can be in a dry state, where no pond soil is having water above. In the wet state, at least some water is present and fish can hatch, grow and reproduce. Eggs produced in a wet period are recruited to the egg bank, as adults lay them in the wet soil. In agreement with available data  (Van Goor 2009 , Polačik et al. 2021 , 2023) , eggs are not developing unless they experience dry, less hypoxic conditions. This can occur with different starting times within the same wet period depending on the location of an egg within the pond extent. The model does not contain explicit temperature effects.
The data on Austrolebias bellottii (Van Dooren & Varela-Lasheras 2018) used to parameterize the embryonic life history were collected at 19. 5C and 20. 5C, while the average annual temperature for their site of origin was 17. 9C (Ingeniero Maschwitz Argentina, Worldclim value used in  Helmstetter et al. 2020 ). The model is coded in R (R Core Team 2020) and the scripts available will become available on https://zenodo. org/ when the manuscript is accepted for publication. In the supplementary information the explanations below are translated into equations for the population dynamics.
We simulate spin relaxation and decoherence due to this mechanism by solving the second-order secular Redfield equation including quadratic spin-phonon coupling terms V αqβq 0 26,38 as implemented in the software MolForge 26 (see Supplementary Note 2 for more details on the workflow). As observed previously for vanadyl compounds  26, 38  , the simulations show the contribution of the modulation of the A tensor to be the leading relaxation mechanism in moderate magnetic fields such as 0. 3 T employed in X-band EPR experiments. We note that the contributions of A and g are relatively close to one another in [VO(TPP)] for the values of the field considered and their contribution to spin-phonon relaxation follows qualitatively similar trends (see Supplementary Figs. 14 15 16 17 18 19 ). Figure  5  reports the predictions of T 1 and T 2 in [VO(TPP)] against the experimental results obtained by inversion recovery and Hahn echo at X-band frequencies  27  (see plotted data points in Supplementary Tables  5, 6 ).
794 keV with an energy resolution δE = 3. 0 meV and Si(12 12 12) with an incoming energy of E = 23. 725 keV and an energy resolution δE = 1. 5 meV. The spectrometer layout, with 9 different analysers within the same scattering plane (~0. 75 deg spacing), enables the detection of 9 different momentum transfer simultaneously. This characteristic of the ID28 instrument increases significantly the BZ sampling, obtained when the additional analysers aligns along a symmetry direction. Data on [VO(TPP)] were collected performing constant-Q energy scans for several Q values along the selected high-symmetry directions. Given the long tails of the Lorentzian-like line-shape of the elastic signal (described with a damped-harmonic-oscillator function), we can only measure |q| ≥ 0. 1 Å -1 , i. e. , not to close to the selected Bragg peaks/Γ points.