Santiago Saura

11.3k total citations · 5 hit papers
101 papers, 8.5k citations indexed

About

Santiago Saura is a scholar working on Ecology, Global and Planetary Change and Nature and Landscape Conservation. According to data from OpenAlex, Santiago Saura has authored 101 papers receiving a total of 8.5k indexed citations (citations by other indexed papers that have themselves been cited), including 84 papers in Ecology, 42 papers in Global and Planetary Change and 35 papers in Nature and Landscape Conservation. Recurrent topics in Santiago Saura's work include Wildlife Ecology and Conservation (70 papers), Wildlife-Road Interactions and Conservation (61 papers) and Land Use and Ecosystem Services (35 papers). Santiago Saura is often cited by papers focused on Wildlife Ecology and Conservation (70 papers), Wildlife-Road Interactions and Conservation (61 papers) and Land Use and Ecosystem Services (35 papers). Santiago Saura collaborates with scholars based in Spain, Italy and Canada. Santiago Saura's co-authors include Örjan Bodin, Marie‐Josée Fortin, Assu Gil‐Tena, María C. Mateo‐Sánchez, Grégoire Dubois, Christine Estreguil, Lucy Bastin, Andrea Mandrici, Luca Battistella and Mikel Gurrutxaga San Vicente and has published in prestigious journals such as Nature Communications, PLoS ONE and Ecology.

In The Last Decade

Santiago Saura

99 papers receiving 8.2k citations

Hit Papers

A new habitat availabilit... 2006 2026 2012 2019 2007 2008 2006 2010 2013 250 500 750

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Santiago Saura Spain 46 6.6k 4.4k 2.2k 1.5k 551 101 8.5k
Kevin McGarigal United States 37 5.6k 0.9× 3.8k 0.9× 3.2k 1.5× 1.8k 1.2× 404 0.7× 88 8.5k
Eric W. Sanderson United States 29 4.8k 0.7× 3.2k 0.7× 2.5k 1.1× 2.0k 1.3× 322 0.6× 66 8.3k
Salit Kark Israel 44 3.6k 0.5× 2.5k 0.6× 2.0k 0.9× 1.3k 0.9× 552 1.0× 121 6.5k
Richard T. Kingsford Australia 48 5.4k 0.8× 2.8k 0.6× 3.8k 1.7× 1.0k 0.7× 285 0.5× 266 8.9k
Emma C. Underwood United States 22 3.5k 0.5× 4.0k 0.9× 3.1k 1.4× 2.2k 1.5× 208 0.4× 41 9.3k
Brad H. McRae United States 29 5.2k 0.8× 2.3k 0.5× 1.5k 0.7× 1.9k 1.2× 242 0.4× 35 7.2k
Jake F. Weltzin United States 47 3.8k 0.6× 4.5k 1.0× 3.3k 1.5× 1.5k 1.0× 128 0.2× 107 9.5k
G. Siriwardena United Kingdom 36 3.5k 0.5× 1.7k 0.4× 2.6k 1.2× 1.2k 0.8× 501 0.9× 115 6.1k
Philip Gibbons Australia 43 2.3k 0.4× 2.6k 0.6× 2.2k 1.0× 813 0.5× 367 0.7× 113 5.3k
Barry R. Noon United States 42 4.9k 0.8× 2.2k 0.5× 3.3k 1.5× 1.7k 1.1× 148 0.3× 134 7.5k

Countries citing papers authored by Santiago Saura

Since Specialization
Citations

This map shows the geographic impact of Santiago Saura's research. 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 Santiago Saura with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Santiago Saura more than expected).

Fields of papers citing papers by Santiago Saura

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Santiago Saura. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Santiago Saura. The network helps show where Santiago Saura may publish in the future.

Co-authorship network of co-authors of Santiago Saura

This figure shows the co-authorship network connecting the top 25 collaborators of Santiago Saura. A scholar is included among the top collaborators of Santiago Saura based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Santiago Saura. Santiago Saura is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Garrote, Germán, Andrea Corradini, Francesca Cagnacci, et al.. (2025). Movement phases make a difference in habitat selection: Iberian lynx diversity of responses to human‐modified landscapes. Journal of Animal Ecology. 94(10). 1983–1996.
2.
Moorter, Bram Van, Ilkka Kivimäki, Manuela Panzacchi, et al.. (2023). Habitat functionality: Integrating environmental and geographic space in niche modeling for conservation planning. Ecology. 104(7). e4105–e4105. 10 indexed citations
3.
Ward, Michelle, Santiago Saura, Brooke Williams, et al.. (2020). Just ten percent of the global terrestrial protected area network is structurally connected via intact land. Nature Communications. 11(1). 4563–4563. 143 indexed citations
4.
Saura, Santiago. (2020). The Habitat Amount Hypothesis implies negative effects of habitat fragmentation on species richness. Journal of Biogeography. 48(1). 11–22. 54 indexed citations
5.
Mateo, Rubén G., et al.. (2019). Looking for an optimal hierarchical approach for ecologically meaningful niche modelling. Ecological Modelling. 409. 108735–108735. 25 indexed citations
6.
Mateo, Rubén G., Aitor Gastón, Olivier Broennimann, et al.. (2019). Hierarchical species distribution models in support of vegetation conservation at the landscape scale. Journal of Vegetation Science. 30(2). 386–396. 47 indexed citations
7.
Saura, Santiago, Bastian Bertzky, Lucy Bastin, et al.. (2019). Global trends in protected area connectivity from 2010 to 2018. Biological Conservation. 238. 108183–108183. 69 indexed citations
8.
Mateo, Rubén G., et al.. (2018). Optimization of forest sampling strategies for woody plant species distribution modelling at the landscape scale. Forest Ecology and Management. 410. 104–113. 16 indexed citations
9.
Saura, Santiago, Bastian Bertzky, Lucy Bastin, et al.. (2018). Protected area connectivity: Shortfalls in global targets and country-level priorities. Biological Conservation. 219. 53–67. 169 indexed citations
10.
Herrera, Lorena, et al.. (2017). Landscape connectivity and the role of small habitat patches as stepping stones: an assessment of the grassland biome in South America. Biodiversity and Conservation. 26(14). 3465–3479. 96 indexed citations
11.
Mateo‐Sánchez, María C., Niko Balkenhol, Sam Cushman, et al.. (2015). Estimating effective landscape distances and movement corridors: comparison of habitat and genetic data. Ecosphere. 6(4). 1–16. 98 indexed citations
12.
Hernández-Moreno, Ángela, Marcelo D. Miranda, Eduardo C. Arellano, Santiago Saura, & Carlos Ovalle. (2014). Landscape dynamics and their effect on the functional connectivity of a Mediterranean landscape in Chile. Ecological Indicators. 48. 198–206. 65 indexed citations
13.
Frate, Ludovico, et al.. (2014). Quantifying Forest Spatial Pattern Trends at Multiple Extents: An Approach to Detect Significant Changes at Different Scales. Remote Sensing. 6(10). 9298–9315. 17 indexed citations
14.
Gil‐Tena, Assu, et al.. (2012). Assessing the role of landscape connectivity in recent woodpecker range expansion in Mediterranean Europe: forest management implications. European Journal of Forest Research. 132(1). 181–194. 21 indexed citations
15.
Saura, Santiago, et al.. (2010). Network analysis to assess landscape connectivity trends: Application to European forests (1990–2000). Ecological Indicators. 11(2). 407–416. 317 indexed citations
18.
Saura, Santiago, et al.. (2006). Comparison and development of new graph-based landscape connectivity indices: towards the priorization of habitat patches and corridors for conservation. Landscape Ecology. 21(7). 959–967. 657 indexed citations breakdown →
19.
Saura, Santiago, et al.. (2005). Forest Fragmentation Estimated from Remotely Sensed Data: Is Comparison Across Scales Possible?. Forest Science. 51(1). 51–63. 52 indexed citations
20.
Saura, Santiago, et al.. (2001). Sensitivity of landscape pattern metrics to map spatial extent. Photogrammetric Engineering & Remote Sensing. 67(9). 1027–1036. 136 indexed citations

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.

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