Summary Despite their critical importance for understanding the local effects of global climate change on biodiversity, glacial microrefugia are not well studied because they are difficult to detect by using classical palaeoecological or population genetics approaches. We used soil macrofossil charcoal analysis to uncover the presence of cryptic glacial refugia for European beech (Fagus sylvatica) and other tree species in the Landes de Gascogne (southwestern France). Using botanical identification and direct radiocarbon dating (140 14C‐dates) of macrofossil charcoal extracted from mineral soils, we reconstructed the glacial and postglacial history of all extant beech stands in the region (n = 11). Soil charcoal macrofossils were found in all sites, allowing the identification of up to at least 14 distinct fire events per site. There was direct evidence of the presence of beech during the last glacial period at three sites. Beech was detected during Heinrich stadial‐1, one of the coldest and driest intervals of the last glacial period in Western Europe. Together with previous results on the genetic structure of the species in the region, these findings suggest that beech persisted in situ in several microrefugia through full glacial and interglacial periods up to the present day.

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The forests of Amazonia are among the most biodiverse on Earth, yet accurately quantifying how species composition varies through space (i.e., beta‐diversity) remains a significant challenge. Here, we use high‐fidelity airborne imaging spectroscopy from the Carnegie Airborne Observatory to quantify a key component of beta‐diversity, the distance decay in species similarity through space, across three landscapes in Northern Peru. We then compared our derived distance decay relationships to theoretical expectations obtained from a Poisson Cluster Process, known to match well with empirical distance decay relationships at local scales. We used an unsupervised machine learning approach to estimate spatial turnover in species composition from the imaging spectroscopy data. We first validated this approach across two landscapes using an independent dataset of forest composition in 49 forest census plots (0.1–1.5 ha). We then applied our approach to three landscapes, which together represented terra firme clay forest, seasonally flooded forest and white‐sand forest. We finally used our approach to quantify landscape‐scale distance decay relationships and compared these with theoretical distance decay relationships derived from a Poisson Cluster Process. We found a significant correlation of similarity metrics between spectral data and forest plot data, suggesting that beta‐diversity within and among forest types can be accurately estimated from airborne spectroscopic data using our unsupervised approach. We also found that estimated distance decay in species similarity varied among forest types, with seasonally flooded forests showing stronger distance decay than white‐sand and terra firme forests. Finally, we demonstrated that distance decay relationships derived from the theoretical Poisson Cluster Process compare poorly with our empirical relationships. Synthesis. Our results demonstrate the efficacy of using high‐fidelity imaging spectroscopy to estimate beta‐diversity and continuous distance decay in lowland tropical forests. Furthermore, our findings suggest that distance decay relationships vary substantially among forest types, which has important implications for conserving these valuable ecosystems. Finally, we demonstrate that a theoretical Poisson Cluster Process poorly predicts distance decay in species similarity as conspecific aggregation occurs across a range of nested scales within larger landscapes.

The forests of western Amazonia are among the most diverse tree communities on Earth, yet this exceptional diversity is distributed highly unevenly within and among communities. In particular, a small number of dominant species account for the majority of individuals, whereas the large majority of species are locally and regionally extremely scarce. By definition, dominant species contribute little to local species richness (alpha diversity), yet the importance of dominant species in structuring patterns of spatial floristic turnover (beta diversity) has not been investigated. Here, using a network of 207 forest inventory plots, we explore the role of dominant species in determining regional patterns of beta diversity (community-level floristic turnover and distance-decay relationships) across a range of habitat types in northern lowland Peru. Of the 2,031 recorded species in our data set, only 99 of them accounted for 50% of individuals. Using these 99 species, it was possible to reconstruct the overall features of regional beta diversity patterns, including the location and dispersion of habitat types in multivariate space, and distance-decay relationships. In fact, our analysis demonstrated that regional patterns of beta diversity were better maintained by the 99 dominant species than by the 1,932 others, whether quantified using species-abundance data or species presence-absence data. Our results reveal that dominant species are normally common only in a single forest type. Therefore, dominant species play a key role in structuring western Amazonian tree communities, which in turn has important implications, both practically for designing effective protected areas, and more generally for understanding the determinants of beta diversity patterns.

The forests of Amazonia are among the most biodiverse plant communities on Earth. Given the immediate threats posed by climate and land-use change, an improved understanding of how this extraordinary biodiversity is spatially organized is urgently required to develop effective conservation strategies. Most Amazonian tree species are extremely rare, but a small number are common across the region. Indeed, just 227 "hyperdominant" species account for more than 50% of all individuals > 10 cm dbh. Yet, the degree to which the phenomenon of hyperdominance is sensitive to tree size, the extent to which the composition of dominant species changes with size-class, and how evolutionary history constrains tree hyperdominance, all remain unknown. Here, we use a unique floristic dataset to show that,

Fungi are talented organisms able to produce several natural products with a wide range of structural and pharmacological activities. The conventional fungal cultivation used in laboratories is too poor to mimic the natural habitats of fungi, and this can partially explain why most of the genes responsible for the production of metabolites are transcriptionally silenced. The use of Histone Deacetylase inhibitors (HDACis) to perturb fungal secondary biosynthetic machinery has proven to be an effective approach for discovering new fungal natural products. The present study relates the effects of suberoylanilide hydroxamic acid (SAHA) and sodium valproate (VS) on the metabolome of Botryosphaeria mamane, an endophytic fungus isolated from Bixa orellana L. UHPLC/HR‐MS analysis, integrated with four metabolomics tools: MS‐DIAL, MS‐FINDER, MetaboAnalyst and GNPS molecular networking, was established. This study highlighted that SAHA and VS changed metabolites in B. mamane, causing upregulation and downregulation of metabolites production. In addition, twelve compounds were detected in the extracts as metabolites structurally correlated to SAHA, indicating its important reactivity in the medium or its metabolism by the fungus. An addition of SAHA induced the production of eight metabolites while VS induced only two metabolites undetected in the control strain. This result illustrates the importance of adding HDACis to a fungal culture in order to induce metabolite production.

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The Andean-Amazonian landscape has been universally recognized for its wide biodiversity, and is considered as global repository of ecosystem services. However, the severe loss of forest cover and rapid reduction of the timber species seriously threaten this ecosystem and biodiversity. In this study, we have modeled the distribution of the ten most exploited timber forest species in Amazonas (Peru) to identify priority areas for forest conservation and restoration. Statistical and cartographic protocols were applied with 4454 species records and 26 environmental variables using a Maximum Entropy model (MaxEnt). The result showed that the altitudinal variable was the main regulatory factor that significantly controls the distribution of the species. We found that nine species are distributed below 1000 m above sea level (a.s.l.), except Cedrela montana, which was distributed above 1500 m a.s.l., covering 40.68%. Eight of 10 species can coexist, and the species with the highest percentage of potential restoration area is Cedrela montana (14.57% from Amazonas). However, less than 1.33% of the Amazon has a potential distribution of some species and is protected under some category of conservation. Our study will contribute as a tool for the sustainable management of forests and will provide geographic information to complement forest restoration and conservation plans.