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The Ecuadorian Amazon holds more biodiversity than most other places on Earth. Palms are a particularly dominant component of the vegetation; however, it remains unknown to what degree the pattern has persisted through time. Here, we investigate the persistence of palm dominance through time and the degree to which past human activities (e.g., fire, cultivation, and forest opening) have affected changes in palm abundances across five regions of the Ecuadorian Amazon. We analyzed soil cores (40-80 cm depth) from each region for charcoal (evidence of past fire) and phytoliths (evidence of past vegetation change). The timings of fires (based on 14 C radiocarbon dates), the occurrence, recurrence, and number of fires (based on charcoal presence and abundance in samples), and the amount of change in palm abundances (based on phytoliths) varied within and between the studied regions. The charcoal and phytolith results indicate the presence of low levels of past human activity at all sites. Our results show that patterns of modern palm hyperdominance found in Amazonian forests have not been persistent through time, and that even low levels of past human activities can affect palm abundance.

Understanding how biotic interactions and environmental filtering mediated by soil properties shape plant community assembly is a major challenge in ecology, especially when studying complex and hyperdiverse ecosystems like tropical forests. To shed light on the influence of both factors, we examined how the edaphic optimum of species (their niche position) related to their edaphic range (their niche breadth) along different environmental gradients and how this translates into functional strategies. Here we tested four scenarios describing the shape of the niche breadth-niche position relationship, including one neutral scenario and three scenarios proposing different relative influences of abiotic and biotic factors on community assembly along a soil resource gradient. To do so, we used soil concentration data for five key nutrients (N, P, Ca, Mg, and K), along with accurate measurements of 14 leaf, stem, and root traits for 246 tree species inventoried in 101 plots located across Eastern (French Guiana) and Western (Peru) Amazonia. We found that species niche breadth increased linearly with species niche position along each soil nutrient gradient. This increase was associated with more resource acquisitive traits in the leaves and the roots for soil N, Ca, Mg, and K concentration, while it was negatively associated with wood density for soil P concentration. These observations agreed with one of our hypothetical scenarios in which species with resource conservation traits are confined to the most nutrient-depleted soils (abiotic filter), but they are outperformed by faster-growing species in more fertile conditions (biotic filter). Our results refine and strengthen support for niche theories of species assembly while providing an integrated approach to improving forest management policies., (© 2023 The Ecological Society of America.)

In species-rich regions and highly speciose genera, the need for species identification and taxonomic recognition has led to the development of emergent technologies. Here, we combine long-term plot data with untargated metabolomics, and morphological and phylogenetic data to describe a new rare species in the hyperdiverse genus of trees Inga Mill. Our combined data show that Inga coleyana is a new lineage splitting from their closest relatives I. coruscans and I. cylindrica . Moreover, analyses of the chemical defensive profile demonstrate that I. coleyana has a very distinctive chemistry from their closest relatives, with I. coleyana having a chemistry based on saponins and I. cylindrica and I. coruscans producing a series of dihydroflavonols in addition to saponins. Finally, data from our network of plots suggest that I. coleyana is a rare and probably endemic taxon in the hyper-diverse genus Inga . Thus, the synergy produced by different approaches, such as long-term plot data and metabolomics, could accelerate taxonomic recognition in challenging tropical biomes., Competing Interests: The authors declare there are no competing interests., (©2022 Guevara Andino et al.)

Evolutionary radiations on oceanic islands have fascinated biologists since Darwin's exploration of the Galápagos archipelago [1, 2]. Island radiations can provide key insights for understanding rapid speciation, including evolutionary patterns and the processes behind them. However, lack of resolution of species relationships has historically hindered their investigation, particularly in the plant kingdom [3-5]. Here, we report a time-calibrated phylogenomic analysis based on genotyping-by-sequencing data [6] of the 15 species of Scalesia (Darwin's giant daisies), an iconic and understudied plant radiation endemic to the Galápagos Islands and considered the plant counterpart to Darwin's finches [1, 7-9]. Results support a Pliocene to early Pleistocene divergence between Scalesia and the closest South American relatives, and rapid diversification of extant Scalesia species from a common ancestor dated to the Middle Pleistocene. Major evolutionary patterns in Scalesia include the following: (1) lack of compliance with the "progression rule" hypothesis, in which earlier diverging lineages are expected to occupy older islands; (2) a predominance of within-island speciation over between-island speciation; and (3) repeated convergent evolution of potentially adaptive traits and habitat preferences on different islands during the course of diversification. Massive sequencing provided the essential framework for investigating evolutionary and ecological processes in the complex natural laboratory of the Galápagos, thereby advancing our understanding of island plant radiations., Competing Interests: Declaration of Interests The authors declare no competing interests., (Copyright © 2020 Elsevier Inc. All rights reserved.)

A new species collected in the lowland forests of the Chocó region of Ecuador, Sloanea cayapensis , is described and illustrated and its morphological similarities with other species of Sloanea are discussed., (Juan Ernesto Guevara Andino, Diana Fernandez-Fernandez.)

We compiled a data set for all tree species collected to date in lowland Amazonian Ecuador in order to determine the number of tree species in the region. This data set has been extensively verified by taxonomists and is the most comprehensive attempt to evaluate the tree diversity in one of the richest species regions of the Amazon. We used four main sources of data: mounted specimens deposited in Ecuadorian herbaria only, specimen records of a large-scale 1-hectare-plot network (60 plots in total), data from the Missouri Botanical Garden Tropicos® database (MO), and literature sources. The list of 2,296 tree species names we provide in this data set is based on 47,486 herbarium records deposited in the following herbaria: Alfredo Paredes Herbarium (QAP), Catholic University Herbarium (QCA), Herbario Nacional del Ecuador (QCNE), Missouri Botanical Garden (MO), and records from an extensive sampling of 29,768 individuals with diameter at breast height (dbh) ≥10 cm recorded in our plot network. We also provide data for the relative abundance of species, geographic coordinates of specimens deposited in major herbaria around the world, whether the species is native or endemic, current hypothesis of geographic distribution, representative collections, and IUCN threat category for every species recorded to date in Amazonian Ecuador. These data are described in Metadata S1 and can be used for macroecological, evolutionary, or taxonomic studies. There are no copyright restrictions; data are freely available for noncommercial scientific use (CC BY 3.0). Please see Metadata S1 (Class III, Section B.1: Proprietary restrictions) for additional information on usage., (© 2019 The Authors. Ecology © 2019 The Ecological Society of America.)

To provide an empirical foundation for estimates of the Amazonian tree diversity, we recently published a checklist of 11,675 tree species recorded to date in the region (ter Steege H, et al. (2016) The discovery of the Amazonian tree flora with an updated checklist of all known tree taxa. Scientific Reports 6:29549). From this total of plant records compiled from public databases and literature, widely used in studies on the Amazonian plant diversity, only 6,727 tree species belong to the first taxonomically-vetted checklist published for the region (Cardoso D, et al. (2017) Amazon plant diversity revealed by a taxonomically verified species list. PNAS 114:10695-10700). The striking difference in these two numbers spurred us to evaluate both lists, in order to release an improved Amazonian tree list; to discuss species inclusion criteria; and to highlight the ecological importance of verifying the occurrence of "non-Amazonian" trees in the region through the localization and identification of specimens. A number of species in the 2016 checklist that are not trees, non-native, synonyms, or misspellings were removed and corresponded to about 23% of the names. Species not included in the taxonomically-vetted checklist but verified by taxonomists to occur in Amazonia as trees were retained. Further, the inclusion of recently recorded/new species (after 2016), and recent taxonomic changes added up to an updated checklist including 10,071 species recorded for the Amazon region and shows the dynamic nature of establishing an authoritative checklist of Amazonian tree species. Completing and improving this list is a long-term, high-value commitment that will require a collaborative approach involving ecologists, taxonomists, and practitioners.

Using complementary metrics to evaluate phylogenetic diversity can facilitate the delimitation of floristic units and conservation priority areas. In this study, we describe the spatial patterns of phylogenetic alpha and beta diversity, phylogenetic endemism, and evolutionary distinctiveness of the hyperdiverse Ecuador Amazon forests and define priority areas for conservation. We established a network of 62 one-hectare plots in terra firme forests of Ecuadorian Amazon. In these plots, we tagged, collected, and identified every single adult tree with dbh ≥10 cm. These data were combined with a regional community phylogenetic tree to calculate different phylogenetic diversity (PD) metrics in order to create spatial models. We used Loess regression to estimate the spatial variation of taxonomic and phylogenetic beta diversity as well as phylogenetic endemism and evolutionary distinctiveness. We found evidence for the definition of three floristic districts in the Ecuadorian Amazon, supported by both taxonomic and phylogenetic diversity data. Areas with high levels of phylogenetic endemism and evolutionary distinctiveness in Ecuadorian Amazon forests are unprotected. Furthermore, these areas are severely threatened by proposed plans of oil and mining extraction at large scales and should be prioritized in conservation planning for this region.

With many sophisticated methods available for estimating migration, ecologists face the difficult decision of choosing for their specific line of work. Here we test and compare several methods, performing sanity and robustness tests, applying to large-scale data and discussing the results and interpretation. Five methods were selected to compare for their ability to estimate migration from spatially implicit and semi-explicit simulations based on three large-scale field datasets from South America (Guyana, Suriname, French Guiana and Ecuador). Space was incorporated semi-explicitly by a discrete probability mass function for local recruitment, migration from adjacent plots or from a metacommunity. Most methods were able to accurately estimate migration from spatially implicit simulations. For spatially semi-explicit simulations, estimation was shown to be the additive effect of migration from adjacent plots and the metacommunity. It was only accurate when migration from the metacommunity outweighed that of adjacent plots, discrimination, however, proved to be impossible. We show that migration should be considered more an approximation of the resemblance between communities and the summed regional species pool. Application of migration estimates to simulate field datasets did show reasonably good fits and indicated consistent differences between sets in comparison with earlier studies. We conclude that estimates of migration using these methods are more an approximation of the homogenization among local communities over time rather than a direct measurement of migration and hence have a direct relationship with beta diversity. As betadiversity is the result of many (non)-neutral processes, we have to admit that migration as estimated in a spatial explicit world encompasses not only direct migration but is an ecological aggregate of these processes. The parameter m of neutral models then appears more as an emerging property revealed by neutral theory instead of being an effective mechanistic parameter and spatially implicit models should be rejected as an approximation of forest dynamics.

While studying ecological patterns at large scales, ecologists are often unable to identify all collections, forcing them to either omit these unidentified records entirely, without knowing the effect of this, or pursue very costly and time-consuming efforts for identifying them. These "indets" may be of critical importance, but as yet, their impact on the reliability of ecological analyses is poorly known. We investigated the consequence of omitting the unidentified records and provide an explanation for the results. We used three large-scale independent datasets, (Guyana/ Suriname, French Guiana, Ecuador) each consisting of records having been identified to a valid species name (identified morpho-species - IMS) and a number of unidentified records (unidentified morpho-species - UMS). A subset was created for each dataset containing only the IMS, which was compared with the complete dataset containing all morpho-species (AMS: = IMS + UMS) for the following analyses: species diversity (Fisher's alpha), similarity of species composition, Mantel test and ordination (NMDS). In addition, we also simulated an even larger number of unidentified records for all three datasets and analyzed the agreement between similarities again with these simulated datasets. For all analyses, results were extremely similar when using the complete datasets or the truncated subsets. IMS predicted ≥91% of the variation in AMS in all tests/analyses. Even when simulating a larger fraction of UMS, IMS predicted the results for AMS rather well. Using only IMS also out-performed using higher taxon data (genus-level identification) for similarity analyses. Finding a high congruence for all analyses when using IMS rather than AMS suggests that patterns of similarity and composition are very robust. In other words, having a large number of unidentified species in a dataset may not affect our conclusions as much as is often thought.