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Topic · Ecology

Wildlife-Road Interactions and Conservation

Wildlife-Road Interactions and Conservation is a research topic within Ecology. Science Explorer counts 12k research works in it since 1950. 20.5% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on the ecological effects of roads on wildlife, including habitat connectivity, wildlife mortality, landscape fragmentation, and conservation planning. It explores the use of graph theory and spatial analysis to understand population connectivity, assess environmental impact, and develop mitigation measures to reduce the negative effects of roads on wildlife populations.

  • Road Ecology
  • Habitat Connectivity
  • Wildlife Mortality
  • Landscape Fragmentation
  • Conservation Planning
  • Graph Theory
  • Mitigation Measures
  • Population Connectivity
  • Spatial Patterns
  • Environmental Impact
Research works
12k
fractional, since 1950
In the world top 10%
2.6k
per year above
Top-10% rate
20.5%
share of its works in the world top 10%
Growth, 2013–17 → 2018–22
+64%
the tick is no change

Which countries lead Wildlife-Road Interactions and Conservation research?

By volume, China and the United States publish the most (829 and 444 works in 2022–2025).

By volume, 2022–2025

  1. 1 China 829 works
  2. 2 United States 444 works
  3. 3 India 270 works
  4. 4 Brazil 244 works
  5. 5 United Kingdom 123 works
  6. 6 Australia 108 works
  7. 7 Spain 98 works
  8. 8 Canada 94 works
  9. 9 Germany 77 works
  10. 10 France 76 works

How concentrated that is

The same countries as shares of everything the list above accounts for. A node where two countries do two thirds of the work and one spread evenly across twelve read alike as a ranking and not at all alike here.

China: 35.1%United States: 18.8%India: 11.4%Brazil: 10.3%6 others listed: 24.4%35%largest
China829 · 35.1%United States444 · 18.8%India270 · 11.4%Brazil244 · 10.3%6 others listed575 · 24.4%

Shares of the rows listed above, not of the whole node.

Which institutions lead Wildlife-Road Interactions and Conservation research?

By volume in 2022–2025, Chinese Academy of Sciences publishes the most Wildlife-Road Interactions and Conservation research, followed by Beijing Normal University and Beijing Forestry University.

Who are the leading researchers in Wildlife-Road Interactions and Conservation?

The most-cited researchers publishing on Wildlife-Road Interactions and Conservation include William J. Sutherland and Gregory P. Asner.

  1. 1 William J. Sutherland United Kingdom 2.4k citations
  2. 2 Gregory P. Asner United States 2.3k citations

Ranked by citations received across their whole record, among researchers with at least three works on this topic.

Where is Wildlife-Road Interactions and Conservation research done?

The largest centres of Wildlife-Road Interactions and Conservation research in 2022–2025 are Beijing (China), Wuhan (China), Nanjing (China) and São Paulo (Brazil). Among places with at least 20 works in it, it is an unusually large share of all research in Dehra Dūn and Guiyang.

Largest cities, 2022–2025

  1. 1 Beijing China 229 works
  2. 2 Wuhan China 46 works
  3. 3 Nanjing China 43 works
  4. 4 São Paulo Brazil 34 works
  5. 5 Shanghai China 33 works
  6. 6 Madrid Spain 28 works
  7. 7 Washington D.C. United States 27 works
  8. 8 Xi'an China 26 works
  9. 9 Guiyang China 26 works
  10. 10 Chengdu China 26 works

Where it is the local speciality

  1. Dehra DūnIN · 20.4 works5.9×
  2. GuiyangCN · 25.9 works5.7×
← less than its size predictsmore →

Location quotient: how much more of its research is in Wildlife-Road Interactions and Conservation than the world average.

See Wildlife-Road Interactions and Conservation on the map

Where is the best place to study Wildlife-Road Interactions and Conservation?

Among universities, judged by research, Beijing Forestry University, Guizhou Normal University and Beijing Normal University score highest, combining excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.

0%20%40%mean 34.91%fractional works in this node (log) →share in the world top 10% →Beijing Forestry University: 18, 43.4%Guizhou Normal University: 13, 42.3%Beijing Normal University: 18, 47.3%Wuhan University: 11, 44.5%Southwest Forestry University: 10, 27.6%University of Chinese Academy of Sciences: 15, 45.3%Wildlife Institute of India: 14, 8.6%China University of Mining and Technology: 12, 42.1%Tribhuvan University: 12, 10.0%China University of Geosciences: 9, 38.0%Beijing Normal Unive…Wuhan UniversityBeijing Forestry Uni…Guizhou Normal Unive…
above the meannear itbelow it

One dot per university in the table below. The upper left is the interesting corner: small places doing unusually strong work.

#UniversityScoreTop 10%SpecialisationWorksGrowth
1 Beijing Forestry UniversityChina 65.943.4%17.9×18 -31.4%
2 Guizhou Normal UniversityChina 64.242.3%37.7×13
3 Beijing Normal UniversityChina 63.047.3%7.5×18 -43.0%
4 Wuhan UniversityChina 52.544.5%2.7×11 +275.9%
5 Southwest Forestry UniversityChina 50.327.6%25.4×10
6 University of Chinese Academy of SciencesChina 49.245.3%2.6×15 +45.5%
7 Wildlife Institute of IndiaIndia 48.48.6%179.7×14 +111.6%
8 China University of Mining and TechnologyChina 46.242.1%4.3×12
9 Tribhuvan UniversityNepal 45.110.0%7.9×12 +521.5%
10 China University of GeosciencesChina 44.238.0%5.4×9

Universities only. Score blends excellence (30%), specialisation (25%), size (20%), growth (15%) and international reach (10%), 2015–2022; growth compares 2010–14 with 2015–19.

Is Wildlife-Road Interactions and Conservation research growing?

Output in 2018–2022 was 64% higher than in 2013–2017, peaking in 2025. The fastest-growing topics are Wildlife-Road Interactions and Conservation.

19801990200020102020
grewheldshrank

The same series as a ribbon — one cell per year, darker for more. The line above answers how much; this answers when.

Which topics inside it are moving

Growth and decline on one axis around a shared zero. Two lists side by side hide the thing that matters: whether the growth dwarfs the decline, or the other way round.