China, Taiwan Province of vs Gambia: Cattle and Buffaloes — Stocks

China, Taiwan Province of
103,573 LSU
in 2023
Gambia
139,425 LSU
in 2023
China, Taiwan Province of rank
140th
Gambia rank
138th

Cattle and Buffaloes — Stocks over time

  • China, Taiwan Province of
  • Gambia
50.0k100.0k150.0k200.0k250.0k300.0k196119922023

How they compare

Gambia currently reports 139,425 LSU against 103,573 LSU in China, Taiwan Province of, a difference of 35,852 LSU.

That makes Gambia's figure about 1.3 times China, Taiwan Province of's.

The two have swapped places 1 time across 63 shared years of data; in 1961 it was China, Taiwan Province of ahead.

China, Taiwan Province of ranks 140th and Gambia ranks 138th of 190 countries.

Across the 7 decades both report, China, Taiwan Province of averaged higher in 2 and Gambia in 5.

Head to head by decade

Decade China, Taiwan Province of Gambia Difference Ahead
1960s 263,021 LSU 96,492 LSU 166,529 LSU China, Taiwan Province of
1970s 165,189 LSU 138,985 LSU 26,204 LSU China, Taiwan Province of
1980s 95,756 LSU 149,960 LSU 54,205 LSU Gambia
1990s 105,525 LSU 174,222 LSU 68,697 LSU Gambia
2000s 95,209 LSU 195,392 LSU 100,182 LSU Gambia
2010s 94,434 LSU 205,750 LSU 111,317 LSU Gambia
2020s 103,141 LSU 141,095 LSU 37,955 LSU Gambia

Averages of every year both report within each decade.

Frequently asked questions

Which has higher cattle and buffaloes — stocks, China, Taiwan Province of or Gambia?
Gambia, at 139,425 LSU against 103,573 LSU in China, Taiwan Province of as of 2023.
What is the difference in cattle and buffaloes — stocks between China, Taiwan Province of and Gambia?
35,852 LSU, with Gambia ahead.
How many years of comparable data are there for China, Taiwan Province of and Gambia?
63 years are reported by both, from 1961 to 2023.
How do China, Taiwan Province of and Gambia rank globally for cattle and buffaloes — stocks?
China, Taiwan Province of ranks 140th and Gambia ranks 138th of 190 countries.
Where does this data come from?
Food and Agriculture Organization of the United Nations, published as Cattle and Buffaloes — Stocks. Statizoid refreshes it automatically from the source and publishes the full history for both places.

Individual pages

Share, cite or embed this page

Cite this page

China, Taiwan Province of vs Gambia: Cattle and Buffaloes — Stocks. Statizoid, drawing on Food and Agriculture Organization of the United Nations. Retrieved 07 September 2026, from https://environment.statizoid.com/compare/cattle-and-buffaloes-stocks/china-taiwan-province-of/gambia-the/

Embed or link this data

Paste this into a page to link back to these figures. The data itself is free to reuse under CC BY-NC-SA 3.0 IGO (FAO); please keep the attribution.

<a href="https://environment.statizoid.com/compare/cattle-and-buffaloes-stocks/china-taiwan-province-of/gambia-the/">China, Taiwan Province of vs Gambia: Cattle and Buffaloes — Stocks</a> — Statizoid

About this data

Indicator
Cattle and Buffaloes — Stocks
Unit
LSU
Source
Food and Agriculture Organization of the United Nations
Licence
CC BY-NC-SA 3.0 IGO (FAO)
Coverage
241 places, 13,793 data points, 1961–2023
Last refreshed

The Livestock Patterns domain of FAOSTAT contains data on livestock numbers, shares of major livestock species and densities of livestock units in the agricultural land area. Values are calculated using Livestock Units (LSU), which facilitate aggregating information for different livestock types. Data are available by country, with global coverage, for the period 1961 to the most recent year available with annual updates. This methodology applies the LSU coefficients reported in the "Guidelines for the preparation of livestock sector reviews" (FAO, 2011). From this publication, LSU coefficients are computed by livestock type and by country. The reference unit used for the calculation of livestock units (=1 LSU) is the grazing equivalent of one adult dairy cow producing 3000 kg of milk annually, fed without additional concentrated foodstuffs. FAOSTAT agri-environmental indicators on livestock patterns closely follow the structure of the indicators in EUROSTAT.