Automated Author ProfileYizhaq, Hezi
Ben-Gurion University of the Negev0000-0001-7573-3303
Yizhaq, Hezi
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: 10.5 (sum of 7 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
No description available
Authors
- Wang, Li ;
- Hou, Chengzhi ;
- Pang, Xianghao ;
- Zhang, Haochen ;
- Yizhaq, Hezi ;
- Mason, Joseph ;
- Lu, Huayu ;
- Xu, Zhiwei
No description available
Authors
- Wang, Li ;
- Hou, Chengzhi ;
- Pang, Xianghao ;
- Zhang, Haochen ;
- Yizhaq, Hezi ;
- Mason, Joseph ;
- Xu, Zhiwei
No description available
Authors
- Wang, Li ;
- Hou, Chengzhi ;
- Pang, Xianghao ;
- Zhang, Haochen ;
- Yizhaq, Hezi ;
- Mason, Joseph ;
- Xu, Zhiwei
No description available
Authors
- Wang, Li ;
- Hou, Chengzhi ;
- Pang, Xianghao ;
- Zhang, Haochen ;
- Yizhaq, Hezi ;
- Mason, Joseph ;
- Lu, Huayu ;
- Xu, Zhiwei
No description available
Authors
- Wang, Li ;
- Hou, Chengzhi ;
- Pang, Xianghao ;
- Zhang, Haochen ;
- Yizhaq, Hezi ;
- Mason, Joseph ;
- Lu, Huayu ;
- Xu, Zhiwei
No description available
Authors
- Wang, Li ;
- Hou, Chengzhi ;
- Pang, Xianghao ;
- Zhang, Haochen ;
- Yizhaq, Hezi ;
- Mason, Joseph ;
- Lu, Huayu ;
- Xu, Zhiwei
Numerical analysis of spatial pattern is widely used in ecology to describe the characteristics of floral and faunal distributions. These methods allow attribution of pattern to causal mechanisms by uncovering the specific signatures of patterns and causal agents. For example, grassland‐gap patterns called fairy circles (FCs) in Namibia and Australia are characterized by highly regular and homogenous distributions across landscapes that show spatially periodic ordering. These FCs have been suggested to be caused by both social insects and competitive plant interactions. We compared eight Namibian and Australian FC patterns and also modeled FCs to 16 patterns of social insect nests in Africa, Australia, and America that include the most regular termite mound patterns known. For pattern‐process inference, we used spatial statistics based on both nearest‐neighbor analysis and neighborhood‐density functions. None of the analyzed insect‐nest distributions attain the spatially periodic ordering that is typical of FCs. The inherently more variable patterns of termite and ant nests are commonly attributable to well documented aspects of the faunal life‐history. Our quantitative evidence from drylands shows that the more variable insect‐nest distributions in water‐limited environments cannot explain the characteristic spatial signature of FCs. The analysis demonstrates the interpretation of scale‐dependent neighborhood‐density functions and that it is the identification of unique spatial signatures in regular patterns that need to be linked to process. While our results cannot verify a specific hypothesis, they support the hypothesis that FCs in these drylands are more likely an emergent vegetation pattern caused by strong plant competition for water.
Authors
- Getzin, Stephan ;
- Yizhaq, Hezi ;
- Cramer, Michael D. ;
- Tschinkel, Walter R.