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Biodiversity and Conservation • Acta Amaz. 52 (1) • Jan-Mar 2022 • https://doi.org/10.1590/1809-4392202101413 linkcopy

Open-access Fast and novel botanical exploration of a 320-km transect in eastern Amazonia using DNA barcoding

AuthorshipSCIMAGO INSTITUTIONS RANKINGS

    ABSTRACT

    We explored a 320-km transect in the Tumucumaque mountain range along the border between southern French Guiana and Brazil, sampling all trees and lianas with DBH ≥ 10 cm in seven 25 x 25-m plots installed near seven boundary milestones. We isolated DNA from cambium tissue and sequenced two DNA barcodes (rbcLa and matK) to aid in species identification. We also collected fertile herbarium specimens from other species (trees/shrubs/herbs) inside and outside the plots. The selected DNA barcodes were useful at the family level but failed to identify specimens at the species level. Based on DNA barcoding identification, the most abundant families in the plots were Burseraceae, Fabaceae, Meliaceae, Moraceae, Myristicaceae and Sapotaceae. One third of the images of sampled plants posted on the iNaturalist website were identified by the community to species level. New approaches, including the sequencing of the ITS region and fast evolving DNA plastid regions, remain to be tested for their utility in the identification of specimens at lower taxonomic levels in floristic inventories in the Amazon region.

    KEYWORDS: DNA barcoding; French Guiana-Brazil border; matK; rbcLa; tree inventory; Tumucumaque

    RESUMO

    Um transecto de 320 km foi explorado na Serra do Tumucumaque, ao longo da fronteira entre o sul da Guiana Francesa e o Brasil por meio da amostragem de todas as árvores e lianas com DAP ≥ 10 cm em sete parcelas de 25 x 25 m instaladas perto de sete marcos fronteiriços. Isolamos DNA de tecido cambial e sequenciamos dois códigos de barra de DNA (rbcLa e matK) para auxiliar na identificação das espécies. Também coletamos espécimes de herbário férteis de outras espécies (árvores/arbustos/ervas) dentro e fora das parcelas. Os códigos de barra de DNA selecionados foram úteis em nível de família, mas não conseguiram identificar espécimes em nível de espécie. Com base na identificação de DNA barcoding, as famílias mais abundantes nas parcelas foram Burseraceae, Fabaceae, Meliaceae, Moraceae, Myristicaceae e Sapotaceae. Um terço das imagens de plantas amostradas postadas no website iNaturalist foram identificadas em nível de espécie. Novas abordagens, incluindo o sequenciamento da região ITS e regiões de DNA plastidial de rápida evolução, ainda precisam ser testadas quanto à sua utilidade na identificação de espécimes até níveis taxonômicos mais baixos em inventários florísticos na região amazônica.

    PALAVRAS-CHAVE: código de barras de DNA; fronteira Guiana Francesa-Brasil; inventário de árvores; matK; rbcLa; Tumucumaque

    INTRODUCTION

    The Amazon region harbours the richest flora of the planet, yet many areas remain under-collected (Prance et al. 2000; Hopkins 2007). As a result, there is still considerable uncertainty about the total number of tree species occurring in this region (Cardoso et al. 2017; Ter Steege et al. 2019). In eastern Amazonia, the upper Jarí River is one of the most poorly sampled areas, which is mostly due to the challenging terrain of the Tumucumaque mountain range (Ter Steege et al. 2013; Zizka et al. 2018), where the tallest trees of Amazonia were recently detected (Gorgens et al. 2019).

    In 2015, a survey team hiked 320 km along the border between French Guiana and Brazil, from the trijunction point with Suriname towards the Oiapoque River (Figure 1). The goals of the expedition were to clarify the exact location of the border (Le Tourneau et al. 2016), to explore the Tumucumaque mountain range, and to test the feasibility of a rapid botanical inventory based primarily on tissue collections and techniques requiring only lightweight equipment. In the past, progress in the knowledge of Amazonian flora has been obtained by establishing transects (Tuomisto et al. 2003; Pitman et al. 2008) and by setting up permanent sampling plots (Blundo et al. 2021). However, the French Guiana-Brazil border remains largely underexplored.

    Figure 1
    Environmental context of the 320-km transect. A - Transect route (in red) overlaid on a topographic map of Eastern Amazonia (SRTM product at 1 arc second resolution; downloaded from the USGS Earth Explorer website); blue-to-red colour ranges from 125 to 775 m a.s.l. within the study area; B - Location of the transect area along the border between southern French Guiana and Brazil; C - Ground elevation along the transect measured by a hand-held GPS unit; D - Plot of the difference between remote-sensed ground elevation (SRTM) and ground elevation (mean difference = 10.6 ± 7.9 standard deviation). This figure is in colour in the electronic version.

    In the RAINFOR network of permanent sampling sites (http://www.rainfor.org/en/map), there is a dearth of data between the mouth of the Jari River and the Nouragues Research Station, which are more than 500 km apart. The Amazon Tree Diversity Network includes more information on the tree diversity of the Tumucumaque mountain range but is limited to the trijunction region (https://atdn.myspecies.info/node/2456). This part of the border between Brazil and French Guiana had been surveyed by the French National Geographical Institute (Institut Geographique National - IGN) in 1956-57. Later, in 1961-62 the binational Brazil/France border commission oversaw the construction of seven milestones on selected sites to demarcate the border (Le Tourneau 2017).

    One method to facilitate the identification of sterile plant material is DNA barcoding, which consists of extracting and sequencing short orthologous DNA sequences for each collected plant, and comparing the obtained sequences to a publicly available reference database (GenBank, maintained by the National Center for Biotechnology Information; https://www.ncbi.nlm.nih.gov/genbank/). This method has proven to be effective for the identification of animal species (Hebert et al. 2003), due to the existence of a mitochondrial DNA region called cytochrome oxidase 1 (CO1). CO1 is a good DNA barcode because it is short enough for Sanger sequencing; it can be sequenced using the same pair of primers flanking the sequence in a wide range of taxonomic groups, and it is variable enough to discriminate between sister species (Hebert et al. 2003).

    In plants, the search for universal DNA barcodes has been more difficult, and several strategies have been tested specifically for Neotropical plants (Gonzalez et al. 2009; Kress et al. 2009). The goal of this contribution is not to debate the utility of DNA barcodes for plant identification, but rather to use this approach to aid the taxonomic identification process. Hollingsworth et al. (2009) recommended the use of a combination of two plastid DNA regions, the first part of the rbcL gene (henceforth rbcLa), and a large fragment of the matK gene. Recently, Lima et al. (2018) conducted a survey on the publicly available DNA sequences from tree species of the flora of São Paulo state in Brazil and generated new sequences of three of the most widely used plant DNA barcodes (rbcL, matK and ITS) for 609 tree species of that flora. However, they did not assess the identification potential of the DNA barcodes they surveyed.

    The primary goal of this contribution was to evaluate the potential of the DNA barcoding approach to aid in the taxonomic identification process in a poorly known tropical area, and to highlight the use of samples from cambium tissue for this purpose. Cambium tissue, as an alternative to collecting inaccessible canopy leaves, has already been used in previous DNA barcoding studies (Colpaert et al. 2005; Tibbits et al. 2006; Gonzalez et al. 2009; Novaes et al. 2009). We report on the results of our botanical exploration in this little explored area of Amazonia along the border of Brazil and French Guiana, including environmental conditions, forest structure and tree inventory. We explored the utility of extracting DNA from cambium tissue and the botanical identification potential of two widely used plant DNA barcodes, namely rbcLa and matK.

    MATERIAL AND METHODS

    The 2015 expedition involved 20 people (including 15 from the 3rd Infantry Regiment of the Foreign Legion, part of the Forces Armées de Guyane) and lasted six weeks, with a weekly re-supply of food (Kew youtube 2016). Milestones were separated by 23-68 km, and given the rugged terrain, the team moved about 10 km per day. The route of the expedition was pre-planned but had to be adapted daily depending on local terrain conditions.

    A hand-held GPS unit (Garmin 62) logged the location of the route. The elevation data provided a good opportunity to test the altimetry data from the Shuttle Radar Topography Mission (SRTM) at 30 m resolution in a little-explored area, and on rugged terrain. Using a Tinytag data logger (temperature and humidity; Gemini data loggers, Scientific House, Terminus Rd, Chichester, UK), we monitored environmental conditions throughout the route.

    The route of the expedition is plotted in Figure 1 (a-b). Elevation measurements recorded with the GPS unit show that the terrain of the Tumucumaque range is rugged, with elevation varying between 200 m to 600 m a.s.l. (Figure 1c). Visual impression of the forest along the route are shown with panoramic photographs (Supplementary Material, Figure S1). Comparing ground data and SRTM data showed that the match in elevation was generally quite good, within 7.9 m (standard deviation), but with a systematic bias: SRTM tends to overestimate the elevation by about 10.6 m (Figure 1d). The Tinytag data logger showed that mean temperature did not display a trend along the transect, but varied principally due to daily variations, from 21°C to 27°C, with a few peaks above 30°C when the team reached tabletop inselbergs (Figure 2). Air humidity was consistently high, reaching 100% at night with a minimum around 80% at mid-day (Figure 3).

    Figure 2
    Air temperature along the transect measured by a Tinytag unit, with daily fluctuations.

    Figure 3
    Example of daily fluctuation of temperature and humidity during the transect route, measured by a Tinytag unit. The data are from 29 Jun 2015, at an altitude of 387 m a.s.l.

    Seven randomised 25 x 25-m (0.0625 ha) plots were established around the seven country-boundary milestones. In each plot, each free-standing stem ≥ 10 cm DBH was sampled for cambium using a cleaned knife, as a rapid alternative to collecting herbarium specimens from trees for identification. Each sampled tree or liana was measured for DBH, and the tree height was recorded on a visual estimation.

    We also sampled fertile material (herbarium specimens) from plants inside and outside the plots, during the march, and from some trees that were felled for a helicopter landing. The herbarium vouchers were deposited at Kew (K) and Cayenne (CAY). The herbarium specimens were directly identified by taxonomists based on morphological features. Field images associated with 167 herbarium specimens were also placed on the iNaturalist website (www.inaturalist.org/observations/willmilliken) to determine whether the specimens could be identified by other experts without knowledge of the corresponding herbarium vouchers. As we did not collect fertile specimens from the trees in the plots, we could not use herbarium identifications to support DNA identification.

    The DNA samples from the cambium of trees and lianas in the plots were used for preliminary identification. These samples did not include the cork, but they did include the cork cambium, the phloem and the vascular cambium together, as recommended by Tibbits et al. (2006). Samples were individually wrapped in tea-filter paper, numbered, and immediately stored in an airtight plastic container with dried silica gel, following a procedure previously described in Gonzalez et al. (2009). A bark slash on each sampled tree, with the tree number, was also photographed. After the end of the trip, samples were shipped for DNA extraction and sequencing.

    For DNA analysis, up to 30 mg of dry tissue of each cambium sample was ground for two minutes in a TissueLyser mixer-mill disruptor (Qiagen, California, USA) using tungsten beads. Lysis incubation was carried out at 65 °C for two hours, using a CTAB 1% PVP buffer. Total DNA extraction was performed with a Biosprint 15 workstation (Qiagen, CA) following the manufacturer’s protocols. PCR amplification was performed for the two plastid DNA barcoding regions selected. The rbcLa marker is the first half of the rbcL gene and was amplified using classic primers: 1F and 724R (Gonzalez et al. 2009). The matK region was amplified using two combinations of primers: 390F and 1326R (Cuénoud et al. 2002); 3F_Kim and 1R_Kim (Dunning and Savolainen 2010; Lima et al. 2018). The PCR reaction mix included 0.2 µl of GoTaq 51 U/µl (Promega), 10 ml of 5 x buffer, 1 µl of 20 µM for each primer, 1 µl of dNTP 10 µM, 1 ml of DNA template and H2O for a final volume of 50 µl. PCR products were purified with a MinElute PCR Purification Kit (Qiagen, CA).

    Cycle sequencing reactions were performed in 10 µl reactions using 1 µl of BigDye Terminator cycle sequencing chemistry (v3.1; ABI; Warrington, Cheshire, UK) and run on an ABI sequencer. The two genetic regions were sequenced in both forward and reverse directions. DNA fragments were visually inspected and assembled with Geneious v.8 and curated manually if necessary. The DNA sequences were then matched with BLAST against the NCBI reference nucleotide collection using Megablast, a plugin available in Geneious. Default options of Megabast were used, and for each sequence, the top hit was visually inspected in the resulting lookup table. The 193 rbcLa sequences were 328-681 nucleotides (nt) in length (three were less than 500 nt). Two sequences had a pairwise sequence similarity < 97%, and they were removed from subsequent analyses. The 227 matK sequences were 123-804 nucleotides in length (nine were less than 500 nt). Two sequences had a pairwise sequence similarity < 97%, and they were also removed from subsequent analyses. All sequences were submitted to NCBI, and GenBank accession numbers are available in the Supplementary Material, Tables S1, S2.

    RESULTS

    Overall, 279 trees were sampled in a total area of 0.4375 ha over the seven plots (Table 1), resulting in an estimated density of 642 trees with DBH ≥ 10 cm per hectare. In addition, 15 lianas were sampled from the plots. Average tree height was 16 m, and average basal area was 38.2 (24 - 58.5) m2 ha-1, with a tendency to smaller basal area in plots at higher elevations (387- 556 m a.s.l.) than the plots at lower elevations (285-366 m a.s.l.). A brief description of the plots is provided in the Supplementary Material (Figure S3).

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    Table 1
    Basal area, maximal DBH, number of trees ≥ 10 cm DBH, and average tree height in each of seven plots (25 m x 25 m) sampled along a 320-km transect on the Brazil-French Guiana border. GPS coordinates of the plots are in WGS 84.

    We extracted DNA sequences for 235 individuals (84.2% of the cambium samples). Mean DNA concentration was 12 ng µL-1, range = 3 - 25 ng µL-1. Of the 235 samples, 197 (83.8%) were amplified for rbcLa, and 220 (93.6%) for matK, with 170 samples (72.3%) amplified for both markers. Matching to the NCBI reference database revealed that most of the specimens could be confidently identified to family.

    Comparing the identifications based on either rbcLa and matK revealed a corresponding match per sample in 98.8% at the family level, 59.1% at the generic level and 10.7% at the species level. Tree taxa identified at the species level were Balizia pedicellaris (DC.) Barneby & J.W.Grimes, Diospyros tetrandra Hiern, Leonia glycycarpa Ruiz & Pav., Ormosia arborea (Vell.) Harms, Pseudopiptadenia suaveolens (Miq.) J.W.Grimes, Rhabdodendron amazonicum (Spruce ex Benth.) Huber, Siparuna decipiens (Tul.) A.DC, Theobroma cacao L. and Trymatococcus oligandrus (Benoist) Lanj., and one species of liana (Hippocratea volubilis L.). Interestingly, one sample was identified by both barcodes as Pouteria campechiana (Kuhn) Baehni, which is not native to the Amazon region (Awang-Kanak and Bakar 2018). Due to the low taxonomic resolution of the DNA barcoding, the overall botanical results are reported at family resolution.

    The most abundant family across the tree samples was Burseraceae (21%), all of them attributed to genus Protium (Daly and Fine 2018), followed by Fabaceae (11%), Meliaceae (8%), Moraceae (8%), Myristicaceae (6%), Sapotaceae (6%) and Vochysiaceae (5%) (Table 2). Together, these families contributed over 50% of all tree individuals in the seven plots. We did not include a survey of lianas, due to the small sample size (Supplementary Material, Tables S1 and S2).

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    Table 2
    List of tree families identified in seven 25x25-m plots along the Brazil-French Guiana border. The numbers refer to individual tree counts; INDET refers to trees that could not be identified through DNA barcoding.

    Thirty-five species (31.8% of cambium samples sequenced with one or both markers) were given tentative identifications (Table 3), based on: 1) DNA barcodes (removing alternative identification for species that are not present in French Guiana or neighbouring countries); 2) conformation from the bark slash (Figure 4) by one of the authors (J. Engel); 3) the species was also collected as a herbarium specimen on the expedition, though not from within the plots. Burseraceae and Meliaceae, however, could only be confidently assigned to family level.

    Figure 4
    Examples of bark slash sampled from trees along the Brazil-French Guiana border for DNA barcoding analysis from cambium tissue. A - Protium sp.; B - Arecaceae; C - Helicostylis pedunculata Benoit; D - Swartzia sp. (possibly Swartzia cf. canescens Torke, based on the bark slash); E - Sapotaceae; F - Sapotaceae; G - Vochysiaceae; H - Conceveiba guianensis Aubl.; I - Brosimum alicastrum S

    Of the 289 herbarium vouchers collected during the expedition, 160 were identified by botanists from CAY and K to species (55%) and 27 to genus only (9%). Of the 167 images of vouchered specimens placed on iNaturalist in 2015, 57 (34%) were identified to species in 2021 and 58 (35%) to genus only (Supplementary Material, Figure S2). Among the determined species, 48 were marked as ‘Research Grade’, meaning that two experts or knowledgeable people have reviewed the observation and agreed.

    DISCUSSION

    The tree composition (at family level) in our plots was comparable with that of the Nouragues Station in Central French Guiana (Poncy et al. 2001), but differs from that of Northern French Guiana, with an under-representation of Chrysobalanaceae and Lecythidaceae. This corresponds to other observations on the decrease in Lecythidaceae species-richness, and the increase in Burseraceae, from north to south in French Guiana (Guitet et al. 2015). Comparing data with other plot surveys in the Amazon, the average basal area was high (Phillips et al. 2004). In other parts of French Guiana, basal areas of 30-35 m2 ha-1 are not uncommon, while lower basal areas (25-30 m2 ha-1) are sometimes found in ancient anthropogenic areas (Odonne et al. 2019). A discussion about the herbarium specimens collected on the expedition (available on request from the authors), and ecology relating to these specimens, are described in Le Tourneau et al. (2016) and in the Supplementary Material (Figure S1, Figure S3).

    Collection of cambium samples for DNA barcoding is quicker, particularly for larger trees, than leaf tissue collection. It also means that leafless trees can be surveyed, e.g., in the dry season. Compared to wood, it was found that the cambium had a higher concentration of DNA than the heartwood or sapwood, although it also had larger amounts of PCR reaction inhibitors (Tang et al. 2011). The cambium samples that we collected were rapidly dried with silica gel, corresponding to the best long-term approach for DNA preservation (Mangaravite et al. 2020), and we indeed found that DNA quality was good, despite the fast collection approach adopted in this work.

    Our low success in species identification using DNA barcodes from cambium samples nevertheless confirm that the selected markers do not fully resolve plants down to species level in all plant families (Gonzalez et al. 2009). Our inability to identify Burseraceae and Meliaceae beyond family level was probably since both families include clades that radiated recently (Fine et al. 2014; Koenen et al. 2015), and therefore the DNA barcodes selected in this study are unable to discriminate the species in these clades sufficiently.

    One illustration of this problem is the identification of one of our specimens as Pouteria campechiana. In NCBI, many species in the genus Pouteria have the same matK and rbcL sequences, perhaps due to a relatively recent radiation of this clade within Sapotaceae, subfamily Chrysophylloideae (De Faria et al. 2017). Our BLAST search against NCBI selected one of the possible species and happened to select one that does not occur in our study area, highlighting one of the problems of relying too much on DNA barcodes for species identification. To avoid this type of geographical bias, we could have downloaded the full NCBI database, select only the species known to occur in the study region, and then run the BLAST search on the regional subset. However, several species of Pouteria cooccur in this region, and this procedure would merely reduce geographical inconsistencies, and not resolve the issue with species identification for Sapotaceae.

    Adding more DNA barcodes to the ones selected here, such as the Internal Transcribed Spacers region of nuclear ribosomal DNA (ITS) or the plastid trnH-psbA intergenic spacer might, in some families, increase the rate of correct identification (Gonzalez et al. 2009; Hollingsworth et al. 2009; Costion et al. 2011; Bolson et al. 2015). In an analysis of plant fragments from Brazilian caves (mainly roots), the ITS2 spacer was believed to be the best marker for identification (Ramalho et al. 2018). More recent studies have shown that ITS2 is likely to become recognised as the standard DNA barcode for plants (Moorhouse-Gann et al. 2018; Miao et al. 2019). However, the ITS region presents specific challenges for plants: the ribosomal cluster which carries the ITS region is present in multiple copies in the plant cell, and many of these copies are non-functional, but appear to be retained in the cell (Feliner and Rosselló 2007; Group et al. 2011). Non-functional ITS copies appear to have a lower GC content and are preferentially selected during PCR and sequencing, creating potential biases (Besnard et al. 2009).

    Identification of trees in forest plots, using herbarium specimens, continues to be problematic. In an analysis of 60 plots in Western Amazonia, over the last 30 years, 25% of specimens were misidentified, and in some difficult genera 50% were incorrect (Baker et al. 2017). One of the issues with species identification within our plots (through DNA barcoding) is that there are large numbers of plant species that have not yet been placed in the NCBI reference collection. Only 31% of known plants have sequences in Genbank, and these were fewer near the Equator (Cornwell et al. 2019), where our survey was carried out. Of the species-rich flora of São Paulo (southeastern Brazil), 58% of tree species have at least one barcoding sequence available, including 35.5% with ITS data (Lima et al. 2018). Based on current accumulation rates, it is possible that 100% species coverage will be achieved within the next 20 years for the São Paulo tree flora, but nevertheless this may not be enough for complete identification in specific taxonomic groups of communities with closely related taxa (Lima et al. 2018). Southern Brazil has been more densely explored and studied than Amazonia, so a high coverage of DNA sequences for the flora of our study area is far from being reached.

    Accurate iNaturalist identification of plant images in a poorly known Amazonian region requires trained researchers. Good-quality images, as shown here, can improve the knowledge of species distribution without collecting herbarium specimens. However, given that our images were available to researchers over five years, and less than half are now identified to species, this is not a rapid way to assess biodiversity. New computer-based image identification resources (AI/machine learning) will probably improve and accelerate biodiversity knowledge (Wäldchen and Mäder 2018), but this will require more ‘training’ of images from poorly known taxa (Van Horn et al. 2018).

    The under-sampling of inter-fluvial areas of Amazonia remains a major hurdle to biodiversity discovery, and future research should prioritize these less accessible areas in a more systematic way to improve conservation planning. In terms of sampling plant diversity, technological development in communication and automated monitoring could bring down the costs of sampling in the future (Mulatu et al. 2017; Draper et al. 2020).

    CONCLUSIONS

    Our study demonstrates that lightweight expeditions can benefit from the advances in novel biodiversity monitoring, yet the impossibility to collect herbarium specimens from trees in such conditions is an impediment to species discovery. Identification of trees using DNA from cambium samples and two DNA barcodes (rbcLa and matK) yielded low success at the species level. Our identifications at the family level are insufficient for comparable surveys across Amazonia. Using DNA barcoding to aid species identification will require further development, not only of sampling methods but also the necessary knowledge to support it (a baseline of accurate and reproducible DNA barcodes). We hope that this research, and the discovery of new techniques, will stimulate increased research in eastern Amazonia.

    ACKNOWLEDGMENTS

    We are grateful to supporters and participants in the expedition and research, including the Parc Amazonien de Guyane, Forces Armées de Guyane (3rd Foreign Infantry Regiment), French National Centre for Scientific Research (CNRS), Ministry of the Interior, National Geographic Institute (IGN), National Museum of Natural History (MNHN) and the IRD Herbarium in Cayenne (CAY). Sponsors included Airbus Defence and Space, Arianespace, Cofely Endel, Kew Foundation, and the National Centre for Space Studies (CNES). This work has benefited from an “Investissement d’Avenir” grant managed by Agence Nationale de la Recherche (CEBA, ref. ANR-10-LABX-25-01).

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    • CITE AS:
      Milliken, W.; Odonne, G.; Engel, J.; Le Tourneau, F.; Suescun, U.; Chave, J. 2022. Fast and novel botanical exploration of a 320-km transect in eastern Amazonia using DNA barcoding. Acta Amazonica 52: 29-37.

    SUPPLEMENTARY MATERIAL

    (only available in the electronic version)

    Milliken et al. Fast and novel botanical exploration of a 320-km transect in eastern Amazonia using DNA barcoding

    Figure S1
    Examples of panoramas of the vegetation along the 320-km transect along the border between southern French Guiana and Brazil. A - 2.324275N, 54.5391W, creek between hills, with Euterpe oleracea Mart., Socratea exorrhiza (Mart.) H.Wendl. (Arecaceae), Symphonia globulifera L.f. (Clusiaceae) and Rapatea paludosa Aubl. (Rapateaceae); B - 2.279289N, 54.5253W, granite inselberg, with Mandevilla surinamensis (Pulle) Woodson (Apocynaceae), Oreopanax capitatus (Jacq.) Decne. & Planch. (Araliaceae), Topobea parasitica Aubl. (Melastomataceae), Clusia palmicida Rich. (Clusiaceae) and Sapium argutum (Müll. Arg.) Huber (Euphorbiaceae); C - 2.256044N, 54.4826W, forest on ridge, with Astrocaryum sciophyllum (Miq.) Pulle (Arecaceae); D - 2.207178N, 54.438W, granite inselberg. In damp areas on the rock the species included Sipanea wilson-brownei R.S. Cowan (Rubiaceae), Paepalanthus oyapockensis Herzog (Eriocaulaceae), Rhynchospora subdicephala T. Koyama (Cyperaceae), Utricularia hispida spp. (Lentibulariaceae), Sinningia incarnata (Aubl.) D.L.Denham (Gesneriaceae), among others; E - 2.168647N, 54.3391W, forest on ridge, with Astrocaryum sciophyllum (Miq.) Pulle (Arecaceae); F - 2.166903N, 54.2006W, forest on ridge, with the massive Huberodendron swietenioides (Gleason) Ducke (Malvaceae); G - 2.207217N, 53.973027W, forest on ridge, dominated by Fabaceae and Meliaceae. Fluted trunks on the left are Minquartia guianensis Aubl. (Olacaceae); H - 2.300701N, 53.885363W, forest on ridge with young stems of Oenocarpus sp. (Arecaceae); I - 2.347966N, 53.804337W, swamp forest dominated by Euterpe oleracea Mart. (Arecaceae); J - 2.369397N, 53.772392W, hilltop forest on inselberg, close to Milestone 4, with Ananas comosus (L.) Merr. (Bromeliaceae), and Syagrus inajai (Spruce) Becc. (Arecaceae) which are possible clues of past human occupations.

    Figure S2
    Examples of specimen identification by other botanists, five years after the images became available on iNaturalist (https://www.inaturalist.org/home). A - Rhabdodendron amazonicum (Spruce ex Benth.) Huber; B - Styrax pallidus A.DC.; C - Elleanthus graminifolius (Barb.Rodr.) Løjtnant; D - Nautilocalyx pictus (Hook.) Sprague; E - Sinningia incarnata (Aubl.) D.L.Denham; F - Maieta poeppigii Mart. ex Cogn.; G - Sapium argutum (Müll.Arg.) Huber; H - Carpotroche longifolia (Poepp.) Benth.

    Figure S3
    Brief description of the seven 25x25-m plots sampled for tree cambium along a 320-km transect along the Brazil-French Guiana border (further details in Table 1). 1 - Forest approximately 100 m from an open granite inselberg, on shallow soil, with few large trees and a low canopy (approx. 15 m). The most abundant tree families were Burseraceae (Protium spp.) and Sapotaceae; 2 - Trees larger than in Plot 1 (DBH and height), and more diverse in families and species and with deeper soil. Several trees were felled next to the clearing (for a helicopter landing), where collections were made. These included: Aspidosperma excelsum Benth. (Apocynaceae), Oenocarpus bacaba Mart. (Arecaceae), Protium morii Daly, Protium robustum (Swart) D.M. Porter, Protium spruceanum (Benth.) Engl. (Burseraceae), Caryocar microcarpum Ducke (Caryocaraceae), Dicorynia guianensisAmshoff, Ormosia amazonica Ducke, Swartzia panacoco (Aubl.) R.S.Cowan (Fabaceae), Goupia glabra Aubl. (Goupiaceae), Licaria debilis (Mez) Kosterm (Lauraceae), Eschweilera coriacea (DC.) S.A.Mori (Lecythidaceae), Trichilia micrantha Benth. (Meliaceae), Trymatococcus oligandrus (Moraceae), Iryanthera sp. (Myristicaceae), Touroulia guianensis Aubl. (Ochnaceae), Rhabdodendron amazonicum (Spruce ex Benth.) Huber (Rhabdodendraceae), Talisia carinata Radlk., Toulicia sp. (Sapindaceae), Manilkara huberi (Ducke) Standl. (Sapotaceae), Styrax cf. macrophyllus Schott ex Pohl (Styracaceae), Coussapoa angustifolia Aubl. and Pourouma minor Benoist (Urticaceae). It is likely that Protium sp. in the DNA identifications may have been one of the three species collected, that all the Arecaceae (DNA) were Oenocarpus bacaba, and that Swartzia sp. (DNA) was S. panacoco (identified correctly by matK); 3 - This was the plot highest in tree density, and second for basal area, with 52.53 m² ha-1, mostly small trees (DBH max = 38.3 cm) of Fabaceae and Meliaceae. Located on top of a little plateau, partly on a slope, and likely an old secondary forest, with few species represented by several individuals, but Protium sp. (Burseraceae), (identified as P. decandrum (Aubl.) Marchand by rbcLa determination) appeared three times and Rhabdodendron amazonicum (Spruce ex Benth.) Huber (Rhabdodendraceae) twice; 4 - Located at the top of an inselberg, but on a draining substrate (not directly on the rocky outcrop), with an open understory and a low tree density (544 trees ha-1). The largest tree was measured on this plot. Dominated by Fabaceae and Myristicaceae, with three individuals of Carapa guianensis Aubl. (Meliaceae); 5 - Located on a ridge. Plot with the fewest trees (density of 528 tree ha-1). Dominated by Burseraceae, with both Protium spp. and Protium excelsior Byng & Christenh. (rbcLa); 6 - Plot with the lowest canopy, with open understory and many small diameter stems. Dominated by Burseraceae and Vochysiaceae, in which Erisma uncinatum Warm. (rbcLa) is probably the most abundant species; 7 - Low-density plot (576 tree ha-1) on a well-drained flatland close to the seventh milestone. Dominated by Burseraceae, with both Protium spp. and Protium excelsior (rbcLa), as in Plot 5.

    Thumbnail
    Table S1
    Blast results for rbcLa DNA barcodes against the NCBI online database for samples from seven 25-m2 plots along a 320-km transect on the Brazil-French Guiana border. ‘Query’ refers to the tree label as given in the field. The two last columns report the best hit sequence (organism name and accession) to the DNA barcode.
    Thumbnail
    Table S2
    Blast results for matK DNA barcodes against the NCBI online database for samples from seven 25-m2 plots along a 320-km transect on the Brazil-French Guiana border. ‘Query’ refers to the tree label as given in the field. The two last columns report the best hit sequence (organism name and accession) to the DNA barcode.

    Edited by

    • ASSOCIATE EDITOR:
      Ricarda Riina

    Publication Dates

    • Publication in this collection
      16 Mar 2022
    • Date of issue
      Jan-Mar 2022

    History

    • Received
      12 May 2021
    • Accepted
      17 Dec 2021
    Creative Common - by 4.0
    This is an open-access article distributed under the terms of the Creative Commons Attribution License
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