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Aim: Palms are iconic and dominant elements of neotropical forests. In the Amazon region, palms have been used and managed by humans for food, material, medicine and other purposes for millennia. It is, however, debated to what extent the structure of modern palm communities reflects long‐term human modification. Here, we investigate the complex interplay of ecological and societal factors that influence the distributions of both human‐used and non‐used palms in western Amazonia. Location: Amazonia. Time period: Present. Major taxa studied: Palms (Arecaceae). Methods: We used Bayesian hierarchical joint species distribution models to predict the distributions and environmental niche dimensions of 78 western Amazonian species, and to explore their relationships with their diversity of human uses and with specific uses (food, construction and medicine). The models were parameterized with a comprehensive set of field‐ and satellite‐derived environmental predictors. Results: Our results suggest that a combination of ecological and anthropogenic factors drive the present‐day distributions of Amazonian palms. The modelled ecological niches of the species revealed use‐related species‐sorting along soil, climatic, accessibility and drainage gradients. We found peaks in the proportions of useful palms and their diversity of uses in fertile soils, close to rivers, and on floodplains. These are habitats favourable for human settlement, although they harbour naturally restricted palm species pools. We also found a negative correlation between predicted palm species richness and number of human uses across western Amazonia. Main conclusions: Soil characteristics, accessibility, and species pool size all contribute to defining palm–human relationships. At the basin scale, the signature of human use on palm communities was predicted to be stronger in the species‐poor south‐west than in central‐western Amazonia. Overall, we conclude that environmental conditions have influenced modern Amazonian palm distributions both directly and indirectly, by regulating human settlement patterns and natural resource use over extended time periods. [ABSTRACT FROM AUTHOR]

Questions: Understanding spatial variation in floristic composition is crucial to quantify the extent, patchiness and connectivity of distinct habitats and their spatial relationships. Broad‐scale variation in floristic composition and the degree of uniqueness of different regions remains poorly mapped and understood in several areas across the globe. We here aim to map vegetation heterogeneity in Amazonia. Location: Middle Juruá river region, Amazonas State, Brazil. Methods: We mapped four plant groups by applying machine learning to scale up locally observed community composition and using environmental and remotely sensed variables as predictors, which were obtained as GIS layers. To quantify how reliable our predictions were, we made an assessment of model transferability and spatial applicability. We also compared our floristic composition map to the official Brazilian national‐level vegetation classification. Results: The overall performance of our floristic models was high for all four plant groups, especially ferns, and the predictions were found to be spatially congruent and highly transferable in space. For some areas, the models were assessed not to be applicable, as the field sampling did not cover the spectral or environmental characteristics of those regions. Our maps show extensive habitat heterogeneity across the region. When compared to the Brazilian vegetation classification, floristic composition was relatively homogeneous within dense forests, while floristic heterogeneity in rainforests classified as open was high. Conclusion: Our maps provide geoecological characterization of the regions and can be used to test biogeographical hypotheses, develop species distribution models and, ultimately, aid science‐based conservation and land‐use planning. [ABSTRACT FROM AUTHOR]

The annual flooding cycle of Amazonian rivers sustains the largest floodplains on Earth, which harbour a unique bird community. Recent studies suggest that habitat specialization drove different patterns of population structure and gene flow in floodplain birds. However, the lack of a direct estimate of habitat affinity prevents a proper test of its effects on population histories. In this work, we used occurrence data, satellite images and genomic data (ultra‐conserved elements) from 24 bird species specialized on a variety of seasonally flooded environments to classify habitat affinities and test its influence on evolutionary histories of Amazonian floodplain birds. We demonstrate that birds with higher specialization in river islands and dynamic environments have gone through more recent demographic expansion and currently have less genetic diversity than floodplain generalist birds. Our results indicate that there is an intrinsic relationship between habitat affinity and environmental dynamics, influencing patterns of population structure, demographic history and genetic diversity. Within the floodplains, historical landscape changes have had more severe impacts on island specialists, making them more vulnerable to current and future anthropogenic changes, as those imposed by hydroelectric dams in the Amazon Basin. [ABSTRACT FROM AUTHOR]

The distributions of plant species are affected by characteristics of their environment, most importantly climate and soils. Ferns and lycophytes (hereafter pteridophytes) are no exception to this general ecological principle. However, until relatively recently, little information has been available about pteridophyte-soil relationships in the tropics. Here we review literature that sheds light on the impact of soil conditions on pteridophyte distribution in the lowland forests of tropical America. We provide examples of both soil-related community-level patterns in species turnover and distributions of individual species and genera along soil gradients. We then discuss the relevance of these patterns for the evolution and diversification of pteridophyte lineages and for practical applications, such as the use of pteridophytes as indicators in classification and mapping of soil-related habitats. Finally, we discuss challenges in filling the gaps of knowledge in pteridophyte-soil relationships and suggest possible solutions for them. [ABSTRACT FROM AUTHOR]

During the Quaternary, Chaco Phytogeographic Domain (Chaco) flora in subtropical South America experienced temperature and humidity fluctuations, primarily driven by wind dynamics, leading to significant shifts in species distribution. The palm Butia yatay is endemic to the Chaco and thrives in areas characterized by a warm–rainy climate and mostly restricted to sandy soils. To investigate the current geographic distribution of suitable habitat for B. yatay while assessing the significance of soil variables, we employed two distinct algorithms in species distribution modeling (SDM). We also determined whether the distribution of B. yatay has changed since the Pleistocene and whether these changes align with previously proposed Pleistocene refugia. In the present SDMs, we considered two separate sets of predictors, one set with bioclimatic variables only and the other set with bioclimatic topographic and soil variables. Additionally, we reconstructed the historical geographic distribution of suitable habitats using bioclimatic data. Our results suggested that the primary determinants of B. yatay's current distribution include precipitation and temperature of the driest month and soil cation exchange capacity. Incorporating soil variables affected the estimated size and range of suitable areas. Projections into the past indicated similar suitable habitat distributions during interglacial periods compared with the present. During the Last Glacial Maximum, climatically suitable habitat may have shifted northward, partially overlapping with previously suggested Pleistocene refugia located between the Paraná and Uruguay Rivers. These findings indicate the main factors driving the distribution and ecology of B. yatay and enhance understanding of subtropical flora shifts during the Quaternary. The approach also may prove valuable for other studies within the Chaco. [ABSTRACT FROM AUTHOR]

Aim To evaluate the relative importance of climatic versus soil data when predicting species distributions for Amazonian plants and to gain understanding of potential range shifts under climate change. Location Amazon rain forest. Methods We produced species distribution models ( SDM) at 5-km spatial resolution for 42 plant species (trees, palms, lianas, monocot herbs and ferns) using species occurrence data from herbarium records and plot-based inventories. We modelled species distribution with Bayesian logistic regression using either climate data only, soil data only or climate and soil data together to estimate their relative predictive powers. For areas defined as unsuitable to species occurrence, we mapped the difference between the suitability predictions obtained with climate-only versus soil-only models to identify regions where climate and soil might restrict species ranges independently or jointly. Results For 40 out of the 42 species, the best models included both climate and soil predictors. The models including only soil predictors performed better than the models including only climate predictors, but we still detected a drought-sensitive response for most of the species. Edaphic conditions were predicted to restrict species occurrence in the centre, the north-west and in the north-east of Amazonia, while the climatic conditions were identified as the restricting factor in the eastern Amazonia, at the border of Roraima and Venezuela and in the Andean foothills. Main conclusions Our results revealed that soil data are a more important predictor than climate of plant species range in Amazonia. The strong control of species ranges by edaphic features might reduce species' abilities to track suitable climate conditions under a drought-increase scenario. Future challenges are to improve the quality of soil data and couple them with process-based models to better predict species range dynamics under climate change. [ABSTRACT FROM AUTHOR]

Amazonia combines semi-continental size with difficult access, so both current ranges of species and their ability to cope with environmental change have to be inferred from sparse field data. Although efficient techniques for modeling species distributions on the basis of a small number of species occurrences exist, their success depends on the availability of relevant environmental data layers. Soil data are important in this context, because soil properties have been found to determine plant occurrence patterns in Amazonian lowlands at all spatial scales. Here we evaluate the potential for this purpose of three digital soil maps that are freely available online: SOTERLAC, HWSD, and SoilGrids. We first tested how well they reflect local soil cation concentration as documented with 1,500 widely distributed soil samples. We found that measured soil cation concentration differed by up to two orders of magnitude between sites mapped into the same soil class. The best map-based predictor of local soil cation concentration was obtained with a regression model combining soil classes from HWSD with cation exchange capacity ( CEC) from SoilGrids. Next, we evaluated to what degree the known edaphic affinities of thirteen plant species (as documented with field data from 1,200 of the soil sample sites) can be inferred from the soil maps. The species segregated clearly along the soil cation concentration gradient in the field, but only partially along the model-estimated cation concentration gradient, and hardly at all along the mapped CEC gradient. The main problems reducing the predictive ability of the soil maps were insufficient spatial resolution and/or georeferencing errors combined with thematic inaccuracy and absence of the most relevant edaphic variables. Addressing these problems would provide better models of the edaphic environment for ecological studies in Amazonia. [ABSTRACT FROM AUTHOR]

There is urgent need for more data on species distributions in order to improve conservation planning. A crucial but challenging aspect of producing high-quality data is the correct identification of organisms. Traditional printed floras and dichotomous keys are difficult to use for someone not familiar with the technical jargon. In poorly known areas, such as Amazonia, they also become quickly outdated as new species are described or ranges extended. Recently, online tools have allowed developing dynamic, interactive, and accessible keys that make species identification possible for a broader public. In order to facilitate identifying plants collected in field inventories, we developed an internet-based free-access tool to identify Amazonian fern species. We focused on ferns, because they are easy to collect and their edaphic affinities are relatively well known, so they can be used as an indicator group for habitat mapping. Our key includes 302 terrestrial and aquatic entities mainly from lowland Amazonian forests. It is a free-access key, so the user can freely choose which morphological features to use and in which order to assess them. All taxa are richly illustrated, so specimens can be identified by a combination of character choices, visual comparison, and written descriptions. The identification tool was developed in Lucid 3.5 software and it is available at http://keyserver.lucidcentral.org:8080/sandbox/keys.jsp. [ABSTRACT FROM AUTHOR]

The number of species is known to decrease from the humid tropics towards drier and colder climates, but how species richness varies along environmental and spatial gradients within the tropical rain forests is not clear. We inventoried 214 transects of 0.25 ha to document species diversity patterns in an example plant group (ferns and lycophytes) across non-inundated rain forests of western and central Amazonia, and assessed how well these conformed with proposed hypotheses about species richness. The observed number of species varied between 6 and 71 per transect. The effective number of species (emphasising the degree of unevenness in species abundances) varied between 1.02 and 8.60, and diversity profiles revealed considerable differences among transects in community structure. Although the density of individuals varied over almost two orders of magnitude, species diversity was better explained by other variables. In particular, within-transect species diversity increased substantially with increasing soil cation concentration. It also increased with soil aluminium concentration, heterogeneity in soil chemistry, annual rainfall and dry season rainfall, and was higher in western than in central Amazonia. Multiple regression models explained up to 70% of the variance in species diversity, but the relationships between species diversity and the environmental gradients became progressively weaker as species abundances were given more weight in the calculation of diversity. Our results conformed to the proposal that site productivity promotes species diversity. This seemed to arise from larger species pools on more fertile soils and in wetter climates, even when it could be expected that the older and more widespread infertile soils would have provided more opportunities for speciation. [ABSTRACT FROM AUTHOR]

Aim: A major problem for conservation in Amazonia is that species distribution maps are inaccurate. Consequently, conservation planning needs to be based on other information sources such as vegetation and soilmaps, which are also inaccurate. We propose and test the use of biotic data on a common and relatively easily inventoried group of plants to infer environmental conditions that can be used to improvemaps of floristic patterns for plants in general. Location: Brazilian Amazonia. Methods: We sampled 326 plots of 250 m × 2 m separated by distances of 1-1800 km. Terrestrial fern individuals were identified and counted. Edaphic data were obtained from soil samples and analysed for cation concentration and texture. Climatic data were obtained from Worldclim. We used a multivariate regression tree to evaluate the hierarchical importance of soils and climate for fern communities and identified significant indicator species for the resultant classification. We then tested how well the edaphic properties of the plots could be predicted on the basis of their floristic composition using two calibration methods, weighted averaging and k-nearest neighbour estimation. Results: Soil cation concentration emerged as the most important variable in the regression tree, whereas soil textural and climatic variation played secondary roles. Almost all the plot classes had several fern species with high indicator values for that class. Soil cation concentration was also the variablemost accurately predicted on the basis of fern community composition (R² = 0.65-0.75 for log-transformed data). Predictive accuracy varied little among the calibration methods, and was not improved by the use of abundance data instead of presence-absence data. Conclusions: Fern species composition can be used as an indicator of soil cation concentration, which can be expected to be relevant also for other components of rain forests. Presence-absence data are adequate for this purpose, which makes the collecting of additional data potentially very rapid. Comparison with earlier studies suggests that edaphic preferences of fern species have good transferability across geographical regions within lowland Amazonia. Therefore, species and environmental data sets already available in the Amazon region represent a good starting point for generating better environmental and floristic maps for conservation planning. [ABSTRACT FROM AUTHOR]

Recognition of the spatial variation in tree species composition is a necessary precondition for wise management and conservation of forests. In the Peruvian Amazonia, this goal is not yet achieved mostly because adequate species inventory data has been lacking. The recently started Peruvian national forest inventory (INFFS) is expected to change the situation. Here, we analyzed genus-level variation, summarized through non-metric multidimensional scaling (NMDS), in a set of 157 INFFS inventory plots in lowland to low mountain rain forests (<2000 m above sea level) using Landsat satellite imagery and climatic, edaphic, and elevation data as predictor variables. Genus-level floristic patterns have earlier been found to be indicative of species-level patterns. In correlation tests, the floristic variation of tree genera was most strongly related to Landsat variables and secondly to climatic variables. We used random forest regression, under varying criteria of feature selection and cross-validation, to predict the floristic composition on the basis of Landsat and environmental data. The best model explained >60% of the variation along NMDS axes 1 and 2 and 40% of the variation along NMDS axis 3. We used this model to predict the three NMDS dimensions at a 450-m resolution over all of the Peruvian Amazonia and classified the pixels into 10 floristic classes using k-means classification. An indicator analysis identified statistically significant indicator genera for 8 out of the 10 classes. The results are congruent with earlier studies, suggesting that the approach is robust and can be applied to other tropical regions, which is useful for reducing research gaps and for identifying suitable areas for conservation. [ABSTRACT FROM AUTHOR]

Several factors have been proposed as drivers of species diversification in the Neotropics, including environmental heterogeneity, the development of drainage systems and historical changes in forest distribution due to climatic oscillations. Here, we investigate which drivers contributed to the evolutionary history and current patterns of diversity of a polymorphic songbird (Arremon taciturnus) that is widely distributed in Amazonian and Atlantic forests as well as in Cerrado gallery and seasonally‐dry forests. We use genomic, phenotypic and habitat heterogeneity data coupled with climatic niche modelling. Results suggest the evolutionary history of the species is mainly related to paleoclimatic changes, although changes in the strength of the Amazon river as a barrier to dispersal, current habitat heterogeneity and geographic distance were also relevant. We propose an ancestral distribution in the Guyana Shield, and recent colonization of areas south of the Amazon river at ~380 to 166 kya, and expansion of the distribution to southern Amazonia, Cerrado and the Atlantic Forest. Since then, populations south of the Amazon River have been subjected to cycles of isolation and possibly secondary contact due to climatic changes that affected habitat heterogeneity and population connectivity. Most Amazonian rivers are not associated with long lasting isolation of populations, but some might act as secondary barriers, susceptible to crossing under specific climatic conditions. Morphological variation, while stable in some parts of the distribution, is not a reliable indicator of genetic structure or phylogenetic relationships. [ABSTRACT FROM AUTHOR]

Species distribution models are required for the research and management of biodiversity in the hyperdiverse tropical forests, but reliable and ecologically relevant digital environmental data layers are not always available. We here assess the usefulness of multispectral canopy reflectance (Landsat) relative to climate data in modelling understory plant species distributions in tropical rainforests. We used a large dataset of quantitative fern and lycophyte species inventories across lowland Amazonia as the basis for species distribution modelling (SDM). As predictors, we used CHELSA climatic variables and canopy reflectance values from a recent basin‐wide composite of Landsat TM/ETM+ images both separately and in combination. We also investigated how species accumulate over sites when environmental distances were expressed in terms of climatic or surface reflectance variables. When species accumulation curves were constructed such that differences in Landsat reflectance among the selected plots were maximised, species accumulated faster than when climatic differences were maximised or plots were selected in a random order. Sixty‐nine species were sufficiently frequent for species distribution modelling. For most of them, adequate SDMs were obtained whether the models were based on CHELSA data only, Landsat data only or both combined. Model performance was not influenced by species' prevalence or abundance. Adding Landsat‐based environmental data layers overall improved the discriminatory capacity of SDMs compared to climate‐only models, especially for soil specialist species. Our results show that canopy surface reflectance obtained by multispectral sensors can provide studies of tropical ecology, as exemplified by SDMs, much higher thematic (taxonomic) detail than is generally assumed. Furthermore, multispectral datasets complement the traditionally used climatic layers in analyses requiring information on environmental site conditions. We demonstrate the utility of freely available, global remote sensing data for biogeographical studies that can aid conservation planning and biodiversity management. [ABSTRACT FROM AUTHOR]

Tropical forests have been subjected to increasing deforestation, leading to severe habitat loss and fragmentation of the landscape. Studies of various plant groups-indicate alteration in species diversity and assemblage composition in response to these impacts. How theses impacts affect ferns and lycophytes, however, is less well known. In this study we evaluate the effects of habitat loss and fragmentation on ferns and lycophytes in lowland non-inundated forests in Ecuadorian Amazonia. We obtained assemblage information from thirteen plots located in gradients of habitat loss and fragmentation (as measured by the landscape fragmentation index: fragindex) and used community and diversity indices to evaluate species responses. We found 3,824 individuals of 55 species. The plot with the highest fragindex value (more than 20% of habitat loss and fragmentation) had the lowest diversity, but the highest diversity was found in plots with fragindex values from 12% to 21% of habitat loss and fragmentation rather than in the landscapes without deforestation. Although community composition varied along the fragindex gradient, species turnover was not significantly related to this index. These results suggest that changes in the landscape caused by deforestation alter the availability of habitats, consequently affecting the distribution patterns of ferns and lycophytes. [ABSTRACT FROM AUTHOR]

Amazonia is extremely biodiverse, but the mechanisms for the origin of this diversity are still under debate. We propose a diversification model for Amazonia based on the interplay of intrinsic clade functional traits, habitat associations and past geological events, using as a model group the species-rich Neotropical family Marantaceae. Our results show that the species richness of the lineage is predicted by functional strategy, rather than clade age, and thus the fast vs. slow growth functional trade-off is a major determinant of clade diversification in Marantaceae. Rapidly growing clades were mostly associated with highly productive habitats, and their origin and diversification dynamics matched the expansion of fertile soils mediated by Andean uplift c. 23 Mya. Fast-growth strategies probably led to fast molecular evolution, speeding up speciation rates and species accumulation, resulting in higher numbers of extant species. Our results indicate that pure allopatric-dispersal models disconnected from past geological and ecological forces may be inadequate for explaining the evolutionary and diversity patterns in Amazonian lowlands. We suggest that a coupling of the functional trait-niche framework with diversification dynamics provides insights into the evolutionary history of tropical forests and helps elucidate the mechanisms underlying the origin and evolution of its spectacular biodiversity. [ABSTRACT FROM AUTHOR]

Aim To examine the relative importance of gradients in soil fertility and rainfall for the phylogenetic structure of Neotropical forest fern communities, and to quantify how much the results are affected by phylogenetic resolution. Location Tropical lowland forests in Brazil (central Amazonia) and Panama (the Panama canal watershed). Methods We inventoried local fern communities at a total of 87 sites to model how their species richness and phylogenetic relatedness varied along gradients in soil fertility and rainfall. We produced a time-calibrated species-level molecular phylogeny of ferns, and quantified the phylogenetic relatedness of species within local communities using Faith's phylogenetic diversity ( PD) and mean phylogenetic diversity ( MPD). Calculations were compared for phylogenies resolved to the species and genus levels. Results (1) We found significant and consistent effects of soil nutrient status on local phylogenetic community structure in both regions. In contrast, phylogenetic structure showed only a weak or no relationship with rainfall. (2) In both regions, MPD declined with increasing soil fertility, which means that fern communities on poor soils consisted, on average, of less closely related lineages than fern communities on rich soils. (3) Different fern genera were over-represented in different sections of the soil nutrient gradient. (4) Qualitatively similar results were obtained whether phylogenies were resolved to the species or the genus level. Main conclusions Our results highlight the importance of edaphic variation in structuring plant communities over evolutionary time-scales. Within the tropical forests studied, the effects of soil variation on local phylogenetic community structure seem to outweigh those of climate. Several fern genera show strong edaphic niche conservatism to either poor or rich soils, whereas many other genera have radiated to span a rather broad edaphic range. PD-based measures are so dominated by deep relationships that genus-level phylogenies are sufficient to investigate these patterns in tropical fern communities. [ABSTRACT FROM AUTHOR]

Questions: Does the floristic composition of trees differ between bamboo forests and adjacent non‐bamboo forests? Can the degree of compositional differences be predicted from differences in canopy reflectance as measured by Landsat satellites? Are the results sensitive to different taxonomical data cleaning strategies, or to which tree‐size class is considered? Are some tree taxa associated with either bamboo or non‐bamboo forests? Location: Peruvian Amazonia. Methods: We used national forestry inventory data to characterise floristic composition of trees at 25 sites. Bamboo and non‐bamboo forests were identified with a pixel‐based time series analysis using the entire Landsat TM/ETM+ archive. To visualise floristic similarity among the plots, we used non‐metric multidimensional scaling. Floristic differences between bamboo and non‐bamboo forests were tested using an analysis of similarity (ANOSIM). Mantel tests were used to assess correlation between floristic turnover and differences in canopy reflectance. We tested the impact of applying three different taxonomic data cleaning strategies and of analysing different tree‐size classes. Finally, we ran an indicator species analysis to identify taxa that were associated with either bamboo or non‐bamboo forests. Results: In floristic ordinations, bamboo‐dominated forests appeared floristically distinct from non‐bamboo forests regardless of the taxonomic cleaning strategy and tree‐size class. This floristic separation was also confirmed through analysis of floristic similarity (ANOSIM). Turnover in floristic composition was strongly correlated with differences in the reflectance values of Landsat bands, especially when using genus‐level rather than species‐level data. Different palm taxa were associated with bamboo (Socratea) and non‐bamboo forests (Iriartea). Conclusions: Floristic differences of trees between bamboo‐dominated and non‐bamboo forests are consistent enough to be observable with different tree‐size classes and taxonomic cleaning strategies. Although coarsening the taxonomic resolution to the genus level may hide ecological detail from the results, the fact that it allows keeping incompletely identified stems in the analyses seems to compensate for this. [ABSTRACT FROM AUTHOR]

Aim: To map and interpret floristic and geoecological patterns across the Amazon basin by combining extensive field data with basin‐wide Landsat imagery and climatic data. Location: Amazonia. Taxon: Ground truth data on ferns and lycophytes; remote sensing results reflect forest canopy properties. Methods: We used field plot data to assess main ecological gradients across Amazonia and to relate floristic ordination axes to soil base cation concentration, Climatologies at High Resolution for the Earth's Land Surface Areas (CHELSA) climatic variables and reflectance values from a basin‐wide Landsat image composite with generalized linear models. Ordination axes were then predicted across all Amazonia using Landsat and CHELSA, and a regional subdivision was obtained using k‐medoid classification. Results: The primary floristic gradient was strongly related to base cation concentration in the soil, and the secondary gradient to climatic variables. The Landsat image composite revealed a tapestry of broad‐scale variation in canopy reflectance characteristics across Amazonia. Ordination axis scores predicted using Landsat and CHELSA variables produced spatial patterns consistent with existing knowledge on soils, geology and vegetation, but also suggested new floristic patterns. The clearest dichotomy was between central Amazonia and the peripheral areas, and the available data supported a classification into at least eight subregions. Main conclusions: Landsat data are capable of predicting soil‐related species compositional patterns of understorey ferns and lycophytes across the Amazon basin with surprisingly high accuracy. Although the exact floristic relationships may differ among plant groups, the observed ecological gradients must be relevant for other plants as well, since surface reflectance recorded by satellites is mostly influenced by the tree canopy. This opens exciting prospects for species distribution modelling, conservation planning, and biogeographical and ecological studies on Amazonian biota. Our maps provide a preliminary geoecological subdivision of Amazonia that can now be tested and refined using field data of other plant groups and from hitherto unsampled areas. [ABSTRACT FROM AUTHOR]

Forest edges are an increasingly common feature of Amazonian landscapes due to human-induced forest fragmentation. Substantial evidence shows that edge effects cause profound changes in forest biodiversity and productivity. However, the broader impacts of edge effects on ecosystem functioning remain unclear. Assessing the three-dimensional arrangement of forest elements has the potential to unveil structural traits that are scalable and closely linked to important functional characteristics of the forest. Using over 600 high-resolution terrestrial laser scanning measurements, we present a detailed assessment of forest structural metrics linked to ecosystem processes such as energy harvesting and light use efficiency. Our results show a persistent change in forest structural characteristics along the edges of forest fragments, which resulted in a significantly lower structural diversity, in comparison with the interior of the forest fragments. These structural changes could be observed up to 35 m from the forest edges and are likely to reflect even deeper impacts on other ecosystem variables such as microclimate and biodiversity. Traits related to vertical plant material allocation were more affected than traits related to canopy height. We demonstrate a divergent response from the forest understory (higher vegetation density close to the edge) and the upper canopy (lower vegetation density close to the edge), indicating that assessing forest disturbances using vertically integrated metrics, such as total plant area index, can lead to an erroneous interpretation of no change. Our results demonstrate the strong potential of terrestrial laser scanning for benchmarking broader-scale (e.g. airborne and space-borne) remote sensing assessments of forest disturbances, as well as to provide a more robust interpretation of biophysical changes detected at coarser resolutions. • The structure of Amazonian forest edges was studied using terrestrial laser scanning. • Edge effects caused a persistent decline in the structural diversity of forest edges. • Disturbances caused by edge effects have a strong vertical heterogeneity. • Height and plant layering metrics combined are important indicators of disturbance. • Large scale remote sensing studies can highly benefit from local scale TLS assessments. [ABSTRACT FROM AUTHOR]