Persistent Identifier
|
doi:10.18710/C9XWRD |
Publication Date
|
2022-03-16 |
Title
| Replication Data for: Natural variation in snow depth and snow melt timing in the High Arctic have implications for soil and plant nutrient status and vegetation composition |
Author
| Moriana Armendariz, Mikel (UiT The Arctic University of Norway) - ORCID: 0000-0001-8251-1338
Cooper, Elisabeth J. (UiT The Arctic University of Norway) - ORCID: 0000-0002-0634-1282
Nilsen, Lennart (UiT The Arctic University of Norway) - ORCID: 0000-0002-3826-3151 |
Point of Contact
|
Use email button above to contact.
Moriana Armendariz, Mikel (UiT The Arctic University of Norway)
Cooper, Elisabeth J. (UiT The Arctic University of Norway) |
Description
| Data used for Moriana-Armendariz et al. 2022- Natural variation in snow depth and snow melt timing in the High Arctic have implications for soil and plant nutrient status and vegetation composition Snow cover is a key component in Arctic ecosystems and will likely be affected by changes in winter precipitation. Increased snow depth and consequent later snowmelt leads to greater microbial mineralization in winter, improving soil and vegetation nutrient status. We studied areas with naturally differing snow depths and date of snowmelt in Adventdalen, Svalbard. Soil properties, plant leaf nutrient status and species composition along with vegetation indices (NDVI) were compared for three snowmelt regimes (Early, Mid and Late). We showed: 1) Late regimes (snow beds) had wetter soils, higher pH and leaves of Bistorta vivipara and Salix polaris had higher concentration of nutrients (nitrogen and d15N). Little to no difference was found in soil nutrient concentrations between snowmelt regimes. 2) Late regimes had highest NDVI values, while those of Early and Mid regimes were similar. 3) Vegetation composition differed between Early and Late regimes, with Dryas octopetala and Luzula arcuata subsp. confusa characterizing the former and Equisetum arvense and Eriophorum scheuchzeri the latter. 4) Trends for plant nutrient contents were similar to those found in a nearby snow manipulation experiment. Snow distribution and time of snowmelt played an important role in determining regional environmental heterogeneity, patchiness in plant community distribution, their species composition and plant phenology. (2021-07-07) |
Subject
| Earth and Environmental Sciences |
Keyword
| Svalbard
Soil properties
NDVI
Plant nutrients
Vegetation composition
Soil nutrients
Nutrient state
Snowmelt
Bistorta vivipara
Salix polaris |
Related Publication
| Moriana-Armendariz et al. 2022- Natural variation in snow depth and snow melt timing in the High Arctic have implications for soil and plant nutrient status and vegetation composition doi: 10.1139/AS-2020-0025 https://doi.org/10.1139/AS-2020-0025 |
Language
| English |
Producer
| UiT The Arctic University of Norway (UiT) https://en.uit.no/ |
Production Date
| 2021-07-07 |
Production Location
| Tromsø |
Contributor
| Data Manager : Moriana Armendariz, Mikel
Project Leader : Cooper, Elisabeth J.
Data Collector : Nilsen, Lennart
Data Collector : Anderson, Helen B.
Data Collector : Baggesen, Nanna S.
Data Collector : Ambus, Per L. |
Funding Information
| The Research Council of Norway: 230970
The FRAM Centre: 362270 |
Distributor
| UiT The Arctic University of Norway (UiT The Arctic University of Norway) https://dataverse.no/dataverse/uit |
Depositor
| Moriana Armendariz, Mikel |
Deposit Date
| 2021-07-07 |
Time Period
| Start Date: 2015-07-15 ; End Date: 2020-09-29 |
Date of Collection
| Start Date: 2015-07-15 ; End Date: 2015-07-20
Start Date: 2019-07-12 ; End Date: 2020-09-29 |
Data Type
| Observational data |
Series
| SNOECO: The SNOECO project has been running since 2006 in Adventdalen (Svalbard)and studies the effect of snow accumulation of the habitat. This is done by the use of snow fences erected perpendicular to the main wind direction. The main focus of the study is plant diversity, phenology and nutrient status, but also soil nutrients, microorganisms and other associated organisms (as parasytes). Many datasets and articles have come out of this project |
Software
| R, Version: 4.1.2 |