DOI: 10.5061/dryad.8931zcs4r
title: Data from: Assessing and improving global grassland restoration: Drivers, current effectiveness, and future design

description: As the UN Decade on Ecosystem Restoration begins, grassland restoration
 projects are being scaled up globally. However, a new generation of
 opportunities and challenges requires a new generation of scientific
 guidance, particularly for grassland ecosystems that need restoration. Our
 meta-analysis indicated that grassland restoration significantly enhances
 biodiversity and ecosystem multifunctionality. However, biodiversity and
 ecosystem multifunctionality both increased in only half of the
 restoration observations, indicating that the effectiveness of global
 grassland restoration needs to be improved. Restoration methods and time
 were identified as important predictors of the effectiveness of grassland
 restoration. To address this, we conducted a multi-objective optimization
 to assess when, where, and how to better implement grassland restoration
 projects globally. This optimization aimed to provide targeted strategies
 for different grassland types and regions, considering the varying
 characteristics and needs of each biome.
description: # Data from: Assessing and improving global grassland restoration:
 Drivers, current effectiveness, and future design Dataset DOI:
 [10.5061/dryad.8931zcs4r](https://doi.org/10.5061/dryad.8931zcs4r) ##
 Description of the data and file structure This is a database about global
 grassland restoration. Including but not limited to grassland restoration
 methods, restoration time, and restoration location. A typical evaluation
 of ecological restoration metrics in published field studies included some
 biodiversity indicators and ecosystem multifunctionality indicators, such
 as biodiversity, productivity, and soil nutrients. Thus, we extracted 20
 variables and then grouped them into two categories (8 biodiversity
 indicators, 13 ecosystem multifunctionality indicators and 3 environmental
 indicators) from the papers to test for recovery levels in grasslands. Our
 data included 8 broad taxonomic groups reflecting biodiversity, including
 mammals, birds, herpetofauna, invertebrates, insects, plants, bacteria and
 fungi. The papers within the database employed a diverse range of indices
 for representing biodiversity. These indices included species richness, as
 well as indices such as the Margalef index, Pielou index, Shannon-Wiener
 diversity index, and Simpson diversity index. Considering the variations
 in the choice and quantity of diversity indices presented by different
 journal articles, we utilized the weighted mean of all biodiversity
 metrics to evaluate the comprehensive impact. These ecological metrics
 were classified as ecosystem multifunctionality indicators, including the
 area covered by vegetation (cover), vegetation height above ground
 (height), the amount of leaf litter on the substrate (litter), aboveground
 biomass (AGB), belowground biomass (BGB), soil organic carbon (SOC), total
 nitrogen (TN), total phosphorus (TP), microbial biomass carbon (MBC),
 microbial biomass nitrogen (MBN), and microbial biomass phosphorus (MBP).
 Because the overall multifunctionality of the ecosystems combined with
 multiple indices could reflect the changes in the ecosystems more
 comprehensively than a single index, we used the weighted equalization
 method for the calculation. The environmental factors included the soil pH
 (pH), bulk density (BD) and soil moisture (SM). Moreover, we also gathered
 and documented data on the grassland restoration methods (Action),
 grassland biome types (Biome), restoration duration (Duration), longitude
 (Lon), latitude (Lat), elevation (ELE), mean annual precipitation (MAP),
 mean annual temperature (MAT) and proportion of clay in soils (Clay). To
 ensure suitable baselines for examination of restoration time sequences,
 restoration duration was defined as the time from the start of recovery of
 degraded grassland to the end or the duration of ongoing grassland
 recovery. Based on the new IUCN global ecosystem typology, the dataset
 encompassed three biome groups to quantify the recovery effectiveness in
 grasslands: savannas and grasslands biomes, deserts and semi-deserts
 biomes, and polar and alpine biomes. The savanna and grassland biomes rank
 among the largest biological communities globally. The deserts and
 semi-deserts biomes consist of ecosystems with low to extremely low
 biomass, existing in arid or semi-arid climates. The polar and alpine
 biomes cover the vast Arctic and Antarctic regions, along with high
 mountainous areas across all continents. In the end, our database
 contained 3214 observations. ### Files and variables #### File:
 source_data_deg.csv **Description:**  ##### Variables * id: number *
 Reference: Paper Title * study: number of paper  *
 Date.of.publication: publication date * Start.time: Experimental start
 time * End.time: Experimental end time * Longitude: Longitude *
 Latitude: Latitude * MAT: mean annual temperature * MAP: mean annual
 precipitation * ALT: altitude * class: Ecosystem classification *
 country: country * continent: continent * action: Grouping of Passive
 Recovery and Active Recovery * Restoration.action: Restoration action *
 recovery.time: recovery time * ecofunction: The effect value of ecosystem
 multifunctionality * ecofunction_var: Variance of ecosystem
 multifunctionality * biodiversity: The effect value of biodiversity *
 biodiversity_var: Variance of biodiversity * NA: blank value