Balancing water yield and water use efficiency between planted and natural forests: A global analysis
Data files
Oct 18, 2024 version files 276.23 KB
-
README.md
1.53 KB
-
Sun_et_al_GCB_data.csv
248.85 KB
-
Sun_et_al_Reference_lists_of_extracted_data.docx
25.85 KB
Abstract
Climate warming is projected to affect hydrological cycle in forest ecosystems and makes the forest-water relationship more controversial. Currently, planted forests are gaining more public attention due to their role in carbon sequestration and wood production relative to natural forests. However, little is known about how the global patterns and drivers of water yield and water use efficiency (WUE) differ between planted and natural forests. Here, we conduct a global analysis to compare water yield and WUE in planted and natural forests using 946 observations from 112 published studies. The results showed that global average water yield coefficient was 0.29 for planted forests and 0.34 for natural forests. Planted forests exhibited lower water yield coefficient (p<0.05) in three climatic regions (arid, dry subhumid and humid regions), but higher (p<0.01) WUE only in arid region, compared with natural forests. Both water yield coefficient and WUE in planted forests were significantly lower (p<0.05) than that in natural forests for stand characteristic groups (stand density, average tree height, leaf area index [LAI] and basal area). Additionally, stand density within the ranging between 1000 to 2000 stem ha-1 can maximize the water yield and WUE in planted and natural forests. Water yield coefficient in planted forests was primarily controlled by the factors related to tree growth (i.e. tree height, DBH), while that of natural forest mainly affected by stand structure (i.e. LAI, stand density, DBH). WUE in planted forest was more sensitive to climate than in natural forests. This work highlights the critical role of natural forests in water supply and the importance of tree species selection and stand management (e.g. stand density adjustment) in plantations in future forest restoration policies and climate change mitigation.
https://doi.org/10.5061/dryad.2v6wwpzxm
Description of the data and file structure
Files and variables
File: Sun_et_al_GCB_data
Description:
Variables
- Variables
- Column A - Sequence
- Column B - Citation of reference
- Column C - Reference
- Column D - Year
- Column E - Arid index
- Column F -Latitude (°)
- Column G - Longitude (°)
- Column H - Dominanted tree species
- Column I - Leaf form
- Column J - Forest type
- Column K - Stand age (year)
- Column L - Stand height (m)
- Column M - Diameter at breast height (DBH, cm)
- Column N - Stand density (stem/ha)
- Column O - Leaf area index (LAI, m2/m2)
- Column P - Basal area (m2/ha)
- Column Q - Precipitation (mm)
- Column R - Evapotranspiration (mm)
- Column S - Mean annual temperature (MAT, ℃)
- Column T - Mean annual precipitation (MAP, mm)
- Column U - Water yield coefficient
- Column V - Gross primary productivity (GPP, gC/m2/yr)
- Column W - Water use efficiency (WUE, gC/kg/H2O)
*Tips: (1)The coordinates in this dataset are the locations of species observations as described in cited publications, and measuring hydrology did not threaten tree species. (2)“NA” in each cell represents the missing value.
File: Sun_et_al_Reference lists of extracted data
Description: Reference lists of extracted data
Peer-reviewed journal articles, book chapters and academic theses on water yield in forests published before December 2023 were searched in the Web of Science, Google Scholar, and the reference lists of identified primary studies or review papers.The keyword combinations in this study were (“primary forest” OR “secondary forest” OR “natural forest” OR “native forest” OR “planted forest” OR afforestation OR forestation OR revegetation OR plantation*) AND (runoff OR “water yield” OR evapotranspiration OR streamflow).
Forest characteristics (stand age [year], DBH [cm], tree height [m], stand density [stem ha-1], LAI [m2 m-2], and basal area [m2 ha-1]) and geographical location (latitude [˚] and longitude [˚]) were obtained from the cited publications when these data are available.
Arid index was provided by Global Land Data Assimilation System (GLDAS) which was resampled to a resolution of 0.005°, and is available for download at (https://doi.org/10.11888/Atmos.tpdc.271832). Annual gross primary productivity (GPP) data from 1982 to 2001 was provided by a revised light use efficiency model (EC-LUE model) and is available for download at (https://doi.org/10.6084/m9.figshare.8942336.v3). Annual GPP after 2001 was obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) MOD17A3HGF V6.1 product (https://doi.org/10.5067/MODIS/MOD17A3HGF.061). To eliminate bias between the two datasets, GPP estimated by EC-LUE model were resampled to ensure that these two GPP datasets had the same resolution (0.005°). Mean annual temperature (MAT) and mean annual precipitation (MAP) were provided by the WorldClim 2.1 dataset at a 10 arc-minute resolution and are available for download at (https://www.worldclim.org/).The average values for the variables of all sites were calculated over a 20-year period (2000–2019).