Dataset Information

Using digital soil maps to infer edaphic affinities of plant species in Amazonia: Problems and prospects.

ABSTRACT: 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.

SUBMITTER: Moulatlet GM

PROVIDER: S-EPMC5648677 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature

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Using digital soil maps to infer edaphic affinities of plant species in Amazonia: Problems and prospects.

Moulatlet Gabriel Massaine GM Zuquim Gabriela G Figueiredo Fernando Oliveira Gouvêa FOG Lehtonen Samuli S Emilio Thaise T Ruokolainen Kalle K Tuomisto Hanna H

Ecology and evolution 20170912 20

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 ...[more]

PMID: 29075463

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Project description:Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km2 resolution for 0-5 and 5-15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km2 pixels (summarized from 8519 unique temperature sensors) across all the world's major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (-0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications.

Project description:BackgroundSoil microbes exist throughout the soil profile and those inhabiting topsoil (0-20 cm) are believed to play a key role in nutrients cycling. However, the majority of the soil microbiology studies have exclusively focused on the distribution of soil microbial communities in the topsoil, and it remains poorly understood through the subsurface soil profile (i.e., 20-40 and 40-60 cm). Here, we examined how the bacterial community composition and functional diversity changes under intensive fertilization across vertical soil profiles [(0-20 cm (RS1), 20-40 cm (RS2), and 40-60 cm (RS3)] in the red soil of pomelo orchard, Pinghe County, Fujian, China.ResultsBacterial community composition was determined by 16S rRNA gene sequencing and interlinked with edaphic factors, including soil pH, available phosphorous (AP), available nitrogen (AN), and available potassium (AK) to investigate the key edaphic factors that shape the soil bacterial community along with different soil profiles. The most dominant bacterial taxa were Proteobacteria, Acidobacteria, Actinobacteria, Chloroflexi, Crenarchaeota, and Bacteriodetes. Bacterial richness and diversity was highest in RS1 and declined with increasing soil depth. The distinct distribution patterns of the bacterial community were found across the different soil profiles. Besides, soil pH exhibited a strong influence (pH ˃AP ˃AN) on the bacterial communities under all soil depths. The relative abundance of Proteobacteria, Actinobacteria, Crenarchaeota, and Firmicutes was negatively correlated with soil pH, while Acidobacteria, Chloroflexi, Bacteriodetes, Planctomycetes, and Gemmatimonadetes were positively correlated with soil pH. Co-occurrence network analysis revealed that network topological features were weakened with increasing soil depth, indicating a more stable bacterial community in the RS1. Bacterial functions were estimated using FAPROTAX and the relative abundance of functional bacterial community related to metabolic processes, including C-cycle, N-cycle, and energy production was significantly higher in RS1 compared to RS2 and RS3, and soil pH had a significant effect on these functional microbes.ConclusionsThis study provided the valuable findings regarding the structure and functions of bacterial communities in red soil of pomelo orchards, and highlighted the importance of soil depth and pH in shaping the soil bacterial population, their spatial distribution and ecological functioning. These results suggest the alleviation of soil acidification by adopting integrated management practices to preserve the soil microbial communities for better ecological functioning.

Dataset Information

Using digital soil maps to infer edaphic affinities of plant species in Amazonia: Problems and prospects.

Publications

Using digital soil maps to infer edaphic affinities of plant species in Amazonia: Problems and prospects.

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