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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 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]

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]

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]

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]

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]