Automated Author ProfilePaola Fortini
Paola Fortini
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 3.5 (sum of 4 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
These data are referrerd to the seedlings of three Quercus cerris woods, namely Selva di Castiglione (SC), Bosco della Ficora (BF) and Bosco di San Leo (BSL), developed in different lithological and physiographic conditions and subjected to different forestry practices in Molise region (Italy). The phenotypic parameters considered in this study were the stem and root length and the leaf area, whereas the plant functional traits (PFTs) were specific leaf area (SLA), leaf dry matter content (LDMC), leaf thickness (Lth) and chlorophyll content (CHL). The measures are reffered to three leaves on each seedling.These numeric data can be analyzed with basic statistical programs. These data can be compared with data collected in other sites.
Authors
- Paola Fortini
These data are referrerd to the seedlings of three Quercus cerris woods, namely Selva di Castiglione (SC), Bosco della Ficora (BF) and Bosco di San Leo (BSL), developed in different lithological and physiographic conditions and subjected to different forestry practices in Molise region (Italy). The phenotypic parameters considered in this study were the stem and root length and the leaf area, whereas the plant functional traits (PFTs) were specific leaf area (SLA), leaf dry matter content (LDMC), leaf thickness (Lth) and chlorophyll content (CHL). The measures are reffered to three leaves on each seedling.These numeric data can be analyzed with basic statistical programs. These data can be compared with data collected in other sites.
Authors
- Paola Fortini
These data are referrerd to the seedlings of three Quercus cerris woods, namely Selva di Castiglione (SC), Bosco della Ficora (BF) and Bosco di San Leo (BSL), developed in different lithological and physiographic conditions and subjected to different forestry practices in Molise region (Italy). The phenotypic parameters considered in this study were the stem and root length and the leaf area, whereas the plant functional traits (PFTs) were specific leaf area (SLA), leaf dry matter content (LDMC), leaf thickness (Lth) and chlorophyll content (CHL). The measures are reffered to three leaves on each seedling.These numeric data can be analyzed with basic statistical programs. These data can be compared with data collected in other sites.
Authors
- Paola Fortini
These data are referrerd to the seedlings of three Quercus cerris woods, namely Selva di Castiglione (SC), Bosco della Ficora (BF) and Bosco di San Leo (BSL), developed in different lithological and physiographic conditions and subjected to different forestry practices in Molise region (Italy). The phenotypic parameters considered in this study were the stem and root length and the leaf area, whereas the plant functional traits (PFTs) were specific leaf area (SLA), leaf dry matter content (LDMC), leaf thickness (Lth) and chlorophyll content (CHL). The measures are reffered to three leaves on each seedling.These numeric data can be analyzed with basic statistical programs. These data can be compared with data collected in other sites.
Authors
- Paola Fortini