Data from: Effects of microclimates on species richness of epiphytic and non-epiphytic bryophytes along a subtropical elevational gradient in China
Data files
Apr 08, 2025 version files 5.27 KB
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Bryophyte_richness.csv
675 B
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Environmental_variables.csv
1.65 KB
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README.md
2.94 KB
Abstract
Aim: Biodiversity patterns along elevational gradients have been well documented for vascular plants and terrestrial vertebrates, but we know relatively little about the elevational patterns of bryophytes and their underlying mechanisms, especially the effect of forest microclimate on epiphytic and non-epiphytic bryophytes. Here we study the influence of microclimate variables on the richness of epiphytic and non-epiphytic species for bryophytes as a whole, and for liverworts and mosses separately, in forests along an elevational gradient ranging from 369 m to 1476 m in Mt. Tianmu, a subtropical region in eastern China.
Location: Mt. Tianmu in eastern China.
Methods: We sampled bryophytes in each of 16 vegetation plots, each in the size of 20 m by 20 m, along the elevational gradient and distinguished between mosses and liverworts and between epiphytic and non-epiphytic species. We measured climate conditions at local sites. Species richness of bryophytes along elevational gradient was related to six microclimate variables, using correlation and regression analyses, and a variation partitioning approach.
Results: Overall, species richness of bryophytes showed a slightly decreasing trend with increasing elevation, and epiphytic and non-epiphytic bryophyte richness showed different elevational patterns. Compared to non-epiphytic bryophytes, species richness of epiphytic bryophytes was more influenced by air microclimate. We also found that species richness of bryophytes was influenced by both microclimate extreme variables and microclimate seasonality variables. In sum, utilizing in-situ air and soil microclimatic monitoring data, our study offering a more accurate reflection of the relationship between bryophyte species richness and their habitats.
Main Conclusions: Our results highlight the importance of considering the ecological differences between mosses and liverworts, and distinguishing between microhabitats of sampled bryophyte assemblages when exploring the patterns and drivers of bryophyte diversity along elevational gradients.
https://doi.org/10.5061/dryad.70rxwdc7s
Description of the data and file structure
This study was conducted in Tianmushan National Nature Reserve (TNNR). Bryophyte field surveys were carried out between April and November 2018 in TNNR. Sixteen forest plots measuring 20 m × 20 m were established along an elevational gradient ranging from 369 m to 1476 m. To obtain data on species richness in a plot as complete as possible, both plot sampling (PS) and floristic habitat sampling (FHS) methods were used in field data collection in TNNR. We investigated epiphytic bryophytes at heights of 0.3 m and 1.5 m and north-facing orientation on each tree by utilizing a subplot with a 20 cm × 20 cm metal frame quadrat containing 100 equal-sized standard grids (Figure 1) for each tree sampled. This design allowed for comparability of samples across different elevations. In each subplot, all bryophyte species were collected and the number of grid cells occupied by each species was recorded. Floristic habitat sampling (FHS) involves using microhabitats within a specific type of mesohabitat as a sampling unit, allowing for a thorough inventory of plant species within a defined area.
At each plot, the soil temperature and moisture variables were monitored 10 cm below ground using the iButton DS1992L-F5 dataloggers (Maxim Integrated Products, USA) with sampling interval set at 15-min intervals. The air temperature and moisture variables were recorded with iButton DS1923-F5 dataloggers (Maxim Integrated Products, USA) with sampling interval set at 2-h intervals. The dataloggers were affixed to the northern aspect of the tree trunk, at 1 m above ground level. All dataloggers were covered by white PVC shields to protect the sensors from direct solar radiation.
File: Bryophyte_richness.csv
Species richness of overall, epiphytic and non-epiphytic bryophytes, liverworts, and mosses in each study plot along elevational gradient.
File: Environmental_variables.csv
We used 12 environmental variables in this study. ATmean: Mean annual air temperature (℃); ATseas: Air temperature seasonality (standard deviation *100); ATmin: Min air temperature of coldest month (℃); AMmean: Mean annual air moisture (%); AMseas: Air moisture seasonality (coefficient of variation); AMmin: Min air moisture of coldest quarter (%); STmean: Mean soil annual temperature (℃); STseas: Soil temperature seasonality (standard deviation *100); STmin: Min soil temperature of coldest month (℃); SMmean: Mean annual soil moisture; SMseas: Soil moisture seasonality (coefficient of variation); SMmin: Min soil moisture of coldest quarter. Temperature seasonality = standard deviation * 100, Moisture seasonality = Coefficient of Variation.