Bats

Spatial conservation prioritisation in data-poor countries: a quantitative sensitivity analysis using multiple taxa
Spatial conservation prioritisation in data-poor countries: a quantitative sensitivity analysis using multiple taxa

Spatial conservation prioritisation in data-poor countries: a quantitative sensitivity analysis using multiple taxa Running title: User decisions affect conservation planning Authors: Ahmed El-Gabbas1*, Francis Gilbert2, Carsten F. Dormann1 1 Department of Biometry and Environmental System Analysis, University of Freiburg, D-79106 Freiburg, Germany 2 School of Life Sciences, University of Nottingham, Nottingham, United Kingdom * Corresponding author – E-Mail: elgabbas@outlook.

Jun 21, 2020

Wrong, but useful: regional species distribution models may not be improved by range-wide data under biased sampling
Wrong, but useful: regional species distribution models may not be improved by range-wide data under biased sampling

Wrong, but useful: regional species distribution models may not be improved by range-wide data under biased sampling Ahmed El-Gabbas Carsten F. Dormann https://doi.org/10.1002/ece3.3834 10.1002/ece3.3834 Species distribution modeling (SDM) is an essential method in ecology and conservation.

Jan 1, 2018

Reliability of species distribution modelling for wildlife conservation in developing countries
Reliability of species distribution modelling for wildlife conservation in developing countries

Main Supervisor:Prof. Carsten F. Dormann, Department of Biometry and Environmental System Analysis, University of Freiburg, Germany. Second Supervisor:Prof. Francis Gilbert, School of Life Sciences, Nottingham University, Nottingham, UK.

Jan 1, 2018

Improved species-occurrence predictions in data-poor regions: using large-scale data and bias correction with down-weighted Poisson regression and Maxent
Improved species-occurrence predictions in data-poor regions: using large-scale data and bias correction with down-weighted Poisson regression and Maxent

El-Gabbas A. & Dormann C. F.: Improved species-occurrence predictions in data-poor regions: using large-scale data and bias correction with down-weighted Poisson regression and Maxent. Ecography DOI: 10.1111/ecog.03149. Appendix 1: Supplementary figures and tables Table A1: The estimated optimum combination of Maxent’s feature classes (FC) and Regularization Multiplier (RM) for each species and bias model type.

Jan 1, 2018

Testing the accuracy of species distribution models using species records from a new field survey
Testing the accuracy of species distribution models using species records from a new field survey

Download PDF Tim Newbold, Tom Reader, Ahmed El-Gabbas, Wiebke Berg, Wael M. Shohdi, Samy Zalat, Sherif Baha El Din & Francis Gilbert 2010 Testing the accuracy of species distribution models using species records from a new field survey

Jan 1, 2010

Mammals of Egypt: atlas, Red Data listing and conservation

My contribution: Mapping, species istribution models, translation, and Red Data assessments. I also helped in the analyses and editing.

Jan 1, 2010

Climate-based models of spatial patterns of species richness in Egypt’s butterfly and mammal fauna
Climate-based models of spatial patterns of species richness in Egypt’s butterfly and mammal fauna

Download PDF Tim Newbold, Francis Gilbert, Samy Zalat, Ahmed El-Gabbas, Tom Reader 2009 Climate-based models of spatial patterns of species richness in Egypt’s butterfly and mammal fauna Journal of Biogeography 36: 2085-95

Jan 1, 2009