Data Integration for Large-Scale Models of Species Distributions

251 indexed citations

Abstract

loading...

About

This paper, published in 2019, received 251 indexed citations. Written by Nick J. B. Isaac, Marta A. Jarzyna, Petr Keil, Philipp H. Boersch‐Supan, Ella Browning, Stephen N. Freeman, Nick Golding, Gurutzeta Guillera‐Arroita, Peter A. Henrys and Susan G. Jarvis covering the research area of Ecological Modeling, Nature and Landscape Conservation and Ecology. It is primarily cited by scholars working on Ecological Modeling (182 citations), Ecology (154 citations) and Nature and Landscape Conservation (105 citations). Published in Trends in Ecology & Evolution.

Countries where authors are citing Data Integration for Large-Scale Models of Species Distributions

Specialization
Citations

This map shows the geographic impact of Data Integration for Large-Scale Models of Species Distributions. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Data Integration for Large-Scale Models of Species Distributions with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Data Integration for Large-Scale Models of Species Distributions more than expected).

Fields of papers citing Data Integration for Large-Scale Models of Species Distributions

Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of Data Integration for Large-Scale Models of Species Distributions. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Data Integration for Large-Scale Models of Species Distributions.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

This paper is also available at doi.org/10.1016/j.tree.2019.08.006.

Explore hit-papers with similar magnitude of impact

Rankless by CCL
2026