Automated Author ProfileBuckley, Lauren
Buckley, Lauren
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: 0.9 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Data supporting the publication: Briscoe, N.J., Morris, S.D., Mathewson, P.D., Buckley, L.B., Jusup, M., Levy, O., Maclean, I.M.D., Pincebourde, S., Riddell, E.A., Roberts, J.A., Schouten, R., Sears, M.W. and Kearney, M.R. (2022), Mechanistic forecasts of species responses to climate change: the promise of biophysical ecology. Glob Change Biol. https://doi.org/10.1111/gcb.16557
Datafiles included & brief description (see README file for additional information) 1. Biophysical_model_lit_review_complete_final.csv Data on biophysical modelling studies included in the review, includes publication details, year, Class (ectotherm, endotherm, both) and whether climate change was considered (Yes, No) as well as details of the software used. Includes data used to generate Figure 3a.
2. Biophysical_model_lit_review_raw_search_results.csv Raw results from literature search identifying potential biophysical modelling studies. These were screened to identify publications to include in the final review set (1).
3. Lizard_snake_traits_data_search_results.csv Results from literature searches using terms relating to different types of functional trait data for lizards and snakes: thermal physiology, hydric physiology, morphology, metabolism and thermoregulatory behaviour. Includes data used to generate Figure 3b.
4. Literature_search.R Code to generate Figure 3.
5. feral_cat_microclimate_data_Fig1.csv Feral cat microclimate data used to generate Figure 1b. Includes hourly observed and predicted temperatures for several locations (sun-surface, shade-surface, burrow).
6. feral_cat_predicted_water_costs_Fig1 Feral cat predicted evaporative water loss data used to generate Figure 1c. Includes predicted daily evaporative water loss for feral cats in several locations (sun-surface, shade-surface, burrow).
*Additional information on how feral cat micrclimate and water costs data were generated can be found in Briscoe, N. J., McGregor, H., Roshier, D., Carter, A., Wintle, B. A., & Kearney, M. R. (2022). Too hot to hunt: Mechanistic predictions of thermal refuge from cat predation risk. Conservation Letters, 15, e12906.
Authors
- BRISCOE, NATALIE ;
- Morris, Shane ;
- Mathewson, Paul ;
- Buckley, Lauren ;
- Jusup, Marko ;
- Levy, Ofir ;
- Maclean, Ilya ;
- Pincebourde, Sylvain ;
- Riddell, Eric ;
- Roberts, Jessica ;
- Schouten, Rafael ;
- Sears, Mike ;
- Kearney, Michael
Data supporting the publication: Briscoe, N.J., Morris, S.D., Mathewson, P.D., Buckley, L.B., Jusup, M., Levy, O., Maclean, I.M.D., Pincebourde, S., Riddell, E.A., Roberts, J.A., Schouten, R., Sears, M.W. and Kearney, M.R. (2022), Mechanistic forecasts of species responses to climate change: the promise of biophysical ecology. Glob Change Biol. https://doi.org/10.1111/gcb.16557
Datafiles included & brief description (see README file for additional information) 1. Biophysical_model_lit_review_complete_final.csv Data on biophysical modelling studies included in the review, includes publication details, year, Class (ectotherm, endotherm, both) and whether climate change was considered (Yes, No) as well as details of the software used. Includes data used to generate Figure 3a.
2. Biophysical_model_lit_review_raw_search_results.csv Raw results from literature search identifying potential biophysical modelling studies. These were screened to identify publications to include in the final review set (1).
3. Lizard_snake_traits_data_search_results.csv Results from literature searches using terms relating to different types of functional trait data for lizards and snakes: thermal physiology, hydric physiology, morphology, metabolism and thermoregulatory behaviour. Includes data used to generate Figure 3b.
4. Literature_search.R Code to generate Figure 3.
5. feral_cat_microclimate_data_Fig1.csv Feral cat microclimate data used to generate Figure 1b. Includes hourly observed and predicted temperatures for several locations (sun-surface, shade-surface, burrow).
6. feral_cat_predicted_water_costs_Fig1 Feral cat predicted evaporative water loss data used to generate Figure 1c. Includes predicted daily evaporative water loss for feral cats in several locations (sun-surface, shade-surface, burrow).
*Additional information on how feral cat micrclimate and water costs data were generated can be found in Briscoe, N. J., McGregor, H., Roshier, D., Carter, A., Wintle, B. A., & Kearney, M. R. (2022). Too hot to hunt: Mechanistic predictions of thermal refuge from cat predation risk. Conservation Letters, 15, e12906.
Authors
- BRISCOE, NATALIE ;
- Morris, Shane ;
- Mathewson, Paul ;
- Buckley, Lauren ;
- Jusup, Marko ;
- Levy, Ofir ;
- Maclean, Ilya ;
- Pincebourde, Sylvain ;
- Riddell, Eric ;
- Roberts, Jessica ;
- Schouten, Rafael ;
- Sears, Mike ;
- Kearney, Michael