In:
Ecological Research, Wiley, Vol. 37, No. 3 ( 2022-05), p. 432-445
Kurzfassung:
We present the largest freely available EcoPlate dataset for Japan, comprising data collected from a network of 33 natural forest sites (77 plots) in regions of East Asia ranging from cool temperate to subtropical. EcoPlate is a 96‐well microplate that contains three repeated sets of 31 response wells with different sole carbon substrates. The utilization of each carbon substrate by the microbial community is quantified by the color density of the well during incubation. EcoPlate can provide a multifunctional index of a soil microbial community. Soil properties (water content, carbon [C] and nitrogen [N] contents, the C/N ratio, and pH) that are essential for interpreting the EcoPlate results were also measured. The network is part of the Forest and Grassland Survey of the Monitoring Sites 1000 Project established by the Ministry of the Environment. Using a standardized protocol, soil was sampled between September and December 2020. A preliminary principal component analysis was performed on the temporal integration of color density using 31 substrates. For the temporal integration, we calculated the cumulative amount of color development by integrating the color density development curve. PC1 contributed 55.6% and is thought to represent the magnitude of the overall absorbance of all substrates. The model of environmental factors including elevation and the model of soil properties, including water content and pH, were selected as the best‐fit models for variation in PC1. EcoPlate data enable the meta‐analysis of comparative studies among forest types and testing community ecology and ecosystem function hypotheses at broad spatial scales. The complete data set for this abstract published in the Data Paper section of the journal is available in electronic format in MetaCat in JaLTER at http://db.cger.nies.go.jp/JaLTER/metacat/metacat/ERDP‐2022‐01.1/jalter‐en.
Materialart:
Online-Ressource
ISSN:
0912-3814
,
1440-1703
DOI:
10.1111/1440-1703.12293
Sprache:
Englisch
Verlag:
Wiley
Publikationsdatum:
2022
ZDB Id:
2023900-2
SSG:
12
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