Top 100 Countries by Pollinator Diversity (Bees and Butterflies), 2025
Pollinator Diversity in 2025: what “species richness” reveals (and what it doesn’t)
Pollinators—especially wild native bees (not managed honey bees) and day-flying butterflies—sit at the junction of biodiversity and food systems. They enable reproduction of wild plants and stabilise yields in many crops by improving fruit set, uniformity, and resilience under weather stress. When pollinator communities lose species, ecosystems become more “fragile”: a few remaining species must carry the same ecological load, and shocks (droughts, pesticide pulses, habitat loss) propagate faster through the landscape.
This ranking focuses on diversity (number of species), not abundance (how many individuals). A country can have high species richness while still experiencing local declines in population sizes. Conversely, a country can have fewer species but strong conservation and stable populations.
Counts are harmonised and rounded for comparability across heterogeneous checklists and occurrence-based compilations. Because entomological sampling is uneven, values should be read as best-available approximations rather than an official census.
Table 1 — Top 10 countries by documented pollinator species richness (2025, ≈)
| Rank | Country | Total pollinator species (≈) |
|---|---|---|
| 1 | Brazil | 5 200 |
| 2 | United States | 4 750 |
| 3 | Peru | 4 300 |
| 4 | Colombia | 4 100 |
| 5 | Mexico | 3 600 |
| 6 | China | 3 600 |
| 7 | Ecuador | 3 500 |
| 8 | Venezuela | 3 150 |
| 9 | Bolivia | 2 950 |
| 10 | Indonesia | 2 650 |
Reading tip: “high rank” often reflects a combination of (1) genuinely species-rich biomes (tropics, mountains, Mediterranean mosaics) and (2) the intensity of scientific documentation. Both matter for what you see in a global list.
Bar chart — Top 20 countries by total pollinator species (bees + butterflies, 2025, ≈)
Patterns behind the ranking: hotspots, biomes, and “documentation bias”
A global pollinator ranking is never just “nature speaking”—it is nature filtered through where people have looked and how countries are structured ecologically. Three forces typically push a country upward:
(1) Tropical and mountain gradients create many microclimates and plant communities, supporting large numbers of specialised bees and butterflies. (2) Habitat mosaics (traditional mixed farming, hedgerows, semi-natural grasslands, forest edges) maintain nectar and nesting resources across seasons. (3) Taxonomic capacity (collections, field surveys, long-running catalogues) increases the share of species that are formally recorded.
The flip side is important: a country can be under-ranked because it is under-sampled—not because it is poor in species. This is especially common in parts of the tropics where many species are likely present but not yet fully described or reliably mapped to national checklists.
How the country totals are constructed (conceptually): bee species and butterfly species documented for each country are compiled from global checklists and quality-controlled occurrence-based products. The “Total pollinator species” is the sum of wild bees + butterflies for the same country. Values are shown as ≈ because taxonomy and country presence lists evolve over time.
Top 100 Countries by Pollinator Diversity (Bees + Butterflies), 2025 (≈)
Table format is kept to three columns for readability on mobile. The third column contains the breakdown for bees and butterflies plus the total.
| Rank | Country | Species breakdown (≈) |
|---|---|---|
| 1 | Brazil | Bees ≈1 900; Butterflies ≈3 300; Total ≈5 200 |
| 2 | United States | Bees ≈4 000; Butterflies ≈750; Total ≈4 750 |
| 3 | Peru | Bees ≈800; Butterflies ≈3 500; Total ≈4 300 |
| 4 | Colombia | Bees ≈900; Butterflies ≈3 200; Total ≈4 100 |
| 5 | Mexico | Bees ≈1 800; Butterflies ≈1 800; Total ≈3 600 |
| 6 | China | Bees ≈1 500; Butterflies ≈2 100; Total ≈3 600 |
| 7 | Ecuador | Bees ≈500; Butterflies ≈3 000; Total ≈3 500 |
| 8 | Venezuela | Bees ≈550; Butterflies ≈2 600; Total ≈3 150 |
| 9 | Bolivia | Bees ≈550; Butterflies ≈2 400; Total ≈2 950 |
| 10 | Indonesia | Bees ≈650; Butterflies ≈2 000; Total ≈2 650 |
| 11 | India | Bees ≈700; Butterflies ≈1 600; Total ≈2 300 |
| 12 | Argentina | Bees ≈1 000; Butterflies ≈1 200; Total ≈2 200 |
| 13 | Australia | Bees ≈1 700; Butterflies ≈420; Total ≈2 120 |
| 14 | South Africa | Bees ≈1 200; Butterflies ≈650; Total ≈1 850 |
| 15 | Democratic Republic of the Congo | Bees ≈500; Butterflies ≈1 100; Total ≈1 600 |
| 16 | Malaysia | Bees ≈350; Butterflies ≈1 200; Total ≈1 550 |
| 17 | Philippines | Bees ≈400; Butterflies ≈1 100; Total ≈1 500 |
| 18 | Kenya | Bees ≈600; Butterflies ≈800; Total ≈1 400 |
| 19 | Tanzania | Bees ≈550; Butterflies ≈850; Total ≈1 400 |
| 20 | Thailand | Bees ≈420; Butterflies ≈900; Total ≈1 320 |
| 21 | Vietnam | Bees ≈380; Butterflies ≈900; Total ≈1 280 |
| 22 | Guatemala | Bees ≈450; Butterflies ≈550; Total ≈1 000 |
| 23 | Papua New Guinea | Bees ≈250; Butterflies ≈950; Total ≈1 200 |
| 24 | Madagascar | Bees ≈300; Butterflies ≈850; Total ≈1 150 |
| 25 | Ethiopia | Bees ≈650; Butterflies ≈650; Total ≈1 300 |
| 26 | Pakistan | Bees ≈450; Butterflies ≈320; Total ≈770 |
| 27 | Costa Rica | Bees ≈280; Butterflies ≈650; Total ≈930 |
| 28 | Panama | Bees ≈250; Butterflies ≈650; Total ≈900 |
| 29 | Myanmar | Bees ≈300; Butterflies ≈950; Total ≈1 250 |
| 30 | Democratic Republic of the Congo | Bees ≈500; Butterflies ≈1 100; Total ≈1 600 |
| 31 | Nigeria | Bees ≈350; Butterflies ≈500; Total ≈850 |
| 32 | Cameroon | Bees ≈380; Butterflies ≈700; Total ≈1 080 |
| 33 | Uganda | Bees ≈450; Butterflies ≈700; Total ≈1 150 |
| 34 | Gabon | Bees ≈250; Butterflies ≈600; Total ≈850 |
| 35 | Ghana | Bees ≈250; Butterflies ≈350; Total ≈600 |
| 36 | Paraguay | Bees ≈350; Butterflies ≈250; Total ≈600 |
| 37 | Guyana | Bees ≈180; Butterflies ≈520; Total ≈700 |
| 38 | Suriname | Bees ≈160; Butterflies ≈520; Total ≈680 |
| 39 | Belize | Bees ≈140; Butterflies ≈340; Total ≈480 |
| 40 | Honduras | Bees ≈300; Butterflies ≈450; Total ≈750 |
| 41 | Nicaragua | Bees ≈260; Butterflies ≈420; Total ≈680 |
| 42 | Cuba | Bees ≈180; Butterflies ≈300; Total ≈480 |
| 43 | Dominican Republic | Bees ≈160; Butterflies ≈260; Total ≈420 |
| 44 | Trinidad and Tobago | Bees ≈120; Butterflies ≈180; Total ≈300 |
| 45 | Jamaica | Bees ≈120; Butterflies ≈150; Total ≈270 |
| 46 | Haiti | Bees ≈120; Butterflies ≈160; Total ≈280 |
| 47 | El Salvador | Bees ≈200; Butterflies ≈260; Total ≈460 |
| 48 | Chile | Bees ≈500; Butterflies ≈180; Total ≈680 |
| 49 | Morocco | Bees ≈500; Butterflies ≈260; Total ≈760 |
| 50 | Algeria | Bees ≈420; Butterflies ≈220; Total ≈640 |
| 51 | Tunisia | Bees ≈220; Butterflies ≈170; Total ≈390 |
| 52 | Egypt | Bees ≈250; Butterflies ≈160; Total ≈410 |
| 53 | Spain | Bees ≈1 000; Butterflies ≈260; Total ≈1 260 |
| 54 | Italy | Bees ≈950; Butterflies ≈280; Total ≈1 230 |
| 55 | France | Bees ≈900; Butterflies ≈250; Total ≈1 150 |
| 56 | Germany | Bees ≈600; Butterflies ≈170; Total ≈770 |
| 57 | Greece | Bees ≈520; Butterflies ≈220; Total ≈740 |
| 58 | Portugal | Bees ≈450; Butterflies ≈160; Total ≈610 |
| 59 | Romania | Bees ≈500; Butterflies ≈160; Total ≈660 |
| 60 | Bulgaria | Bees ≈420; Butterflies ≈150; Total ≈570 |
| 61 | Poland | Bees ≈420; Butterflies ≈130; Total ≈550 |
| 62 | Ukraine | Bees ≈380; Butterflies ≈150; Total ≈530 |
| 63 | Russia | Bees ≈650; Butterflies ≈350; Total ≈1 000 |
| 64 | Turkey | Bees ≈700; Butterflies ≈450; Total ≈1 150 |
| 65 | Iran | Bees ≈650; Butterflies ≈350; Total ≈1 000 |
| 66 | Japan | Bees ≈450; Butterflies ≈240; Total ≈690 |
| 67 | Saudi Arabia | Bees ≈220; Butterflies ≈110; Total ≈330 |
| 68 | Yemen | Bees ≈170; Butterflies ≈80; Total ≈250 |
| 69 | Israel | Bees ≈190; Butterflies ≈90; Total ≈280 |
| 70 | Lebanon | Bees ≈150; Butterflies ≈65; Total ≈215 |
| 71 | Jordan | Bees ≈140; Butterflies ≈55; Total ≈195 |
| 72 | Iraq | Bees ≈180; Butterflies ≈75; Total ≈255 |
| 73 | Kazakhstan | Bees ≈320; Butterflies ≈120; Total ≈440 |
| 74 | Uzbekistan | Bees ≈260; Butterflies ≈100; Total ≈360 |
| 75 | Kyrgyzstan | Bees ≈220; Butterflies ≈95; Total ≈315 |
| 76 | Tajikistan | Bees ≈180; Butterflies ≈80; Total ≈260 |
| 77 | Nepal | Bees ≈260; Butterflies ≈220; Total ≈480 |
| 78 | Bhutan | Bees ≈160; Butterflies ≈220; Total ≈380 |
| 79 | Sri Lanka | Bees ≈180; Butterflies ≈240; Total ≈420 |
| 80 | Bangladesh | Bees ≈200; Butterflies ≈160; Total ≈360 |
| 81 | Afghanistan | Bees ≈280; Butterflies ≈140; Total ≈420 |
| 82 | Canada | Bees ≈900; Butterflies ≈300; Total ≈1 200 |
| 83 | United Kingdom | Bees ≈300; Butterflies ≈80; Total ≈380 |
| 84 | Sweden | Bees ≈300; Butterflies ≈100; Total ≈400 |
| 85 | Norway | Bees ≈220; Butterflies ≈70; Total ≈290 |
| 86 | Finland | Bees ≈240; Butterflies ≈90; Total ≈330 |
| 87 | Switzerland | Bees ≈350; Butterflies ≈120; Total ≈470 |
| 88 | Austria | Bees ≈320; Butterflies ≈110; Total ≈430 |
| 89 | Czechia | Bees ≈300; Butterflies ≈90; Total ≈390 |
| 90 | Hungary | Bees ≈320; Butterflies ≈110; Total ≈430 |
| 91 | Serbia | Bees ≈260; Butterflies ≈95; Total ≈355 |
| 92 | Croatia | Bees ≈240; Butterflies ≈110; Total ≈350 |
| 93 | Slovenia | Bees ≈260; Butterflies ≈115; Total ≈375 |
| 94 | Netherlands | Bees ≈220; Butterflies ≈55; Total ≈275 |
| 95 | Belgium | Bees ≈200; Butterflies ≈60; Total ≈260 |
| 96 | Denmark | Bees ≈190; Butterflies ≈55; Total ≈245 |
| 97 | New Zealand | Bees ≈320; Butterflies ≈60; Total ≈380 |
| 98 | Albania | Bees ≈210; Butterflies ≈95; Total ≈305 |
| 99 | North Macedonia | Bees ≈220; Butterflies ≈110; Total ≈330 |
| 100 | Bosnia and Herzegovina | Bees ≈200; Butterflies ≈105; Total ≈305 |
Important limitation: “Top 100” should be seen as a comparative lens, not a final verdict. Many countries likely have higher true richness than currently documented, particularly where surveys and taxonomic work are limited.
Table 2 — Land-use pressure snapshot (agricultural land share vs pollinator richness)
Agricultural land share is used as a simple proxy for landscape conversion and management intensity. Values are rounded ≈ (typically 2022–2023 range in WDI). It is not a direct measure of pesticide load, monoculture structure, or habitat quality—those can move in different directions even at the same land share.
| Country | Agricultural land (% of land area, ≈) | Total pollinator species (≈) |
|---|---|---|
| Brazil | 33 | 5 200 |
| United States | 44 | 4 750 |
| Peru | 19 | 4 300 |
| Colombia | 35 | 4 100 |
| Mexico | 55 | 3 600 |
| China | 56 | 3 600 |
| Indonesia | 31 | 2 650 |
| India | 60 | 2 300 |
| Australia | 53 | 2 120 |
| South Africa | 80 | 1 850 |
| Spain | 52 | 1 260 |
| Malaysia | 24 | 1 550 |
Scatter — Pollinator richness vs agricultural land share (illustrative cross-country relationship)
How to interpret the scatter: if pollinator richness were driven only by how much land is farmed, points would line up neatly. They do not, because biodiversity is also shaped by biogeography (tropics vs temperate zones), topography, and habitat heterogeneity. Yet the scatter is still useful: it makes “pressure vs capacity” visible. Countries that combine high richness with high agricultural land share are often those where large wild areas remain, or where farming landscapes still include edges, fallows, small patches of semi-natural vegetation, and multi-crop mosaics. Countries with low richness at high land share may reflect genuinely lower species pools, but can also signal severe habitat simplification or under-documentation.
A practical takeaway for readers: this ranking is a strong starting point for “bee-friendly” and “butterfly-friendly” stories (community initiatives, school projects, conservation planning), but meaningful comparisons should always be paired with context on habitats, research coverage, and land management.
What this ranking means for policy, agriculture, and public action
Pollinator diversity is often treated as an environmental “nice to have”. In practice, it functions more like a risk management asset for food systems and landscapes. Species-rich pollinator communities provide redundancy: when one species fails in a given year (climate anomaly, disease, pesticide exposure, mismatch with flowering), other species can partially compensate. This stabilising role matters most in crops and regions that depend heavily on insect pollination and in farming systems that face increasing climate volatility.
At a national level, higher documented richness can signal two different realities: a genuinely diverse ecological base, and/or strong capacity to monitor and catalogue species. Both are valuable. Biodiversity without monitoring is hard to defend; monitoring without habitat is hard to sustain.
Technical note: the country figures shown in this article are designed for comparative analysis and education. They should not be used as a substitute for official national inventories, which may differ due to taxonomy updates, regional exclusions, or differing definitions of “presence”.
Policy takeaway: practical implications of pollinator diversity rankings
- Protect habitat mosaics, not only reserves. Many bees and butterflies depend on edges, grasslands, fallows, hedgerows, and seasonal flowering continuity. Policy instruments that preserve “small structures” can be disproportionately effective.
- Measure management intensity, not just land share. Agricultural land percentage is a coarse proxy. What often drives decline is the combination of monoculture simplification, pesticide regimes, and loss of nesting sites. Better monitoring indicators include flower resource continuity, semi-natural cover, and pesticide risk profiles.
- Invest in taxonomy and monitoring capacity. Under-documented countries can appear “low-diversity” simply because the species list is incomplete. Supporting collections, surveys, and open biodiversity data pipelines is a direct way to improve decision quality.
- Target “pollination security” as food-system resilience. Where pollinator communities are simplified, crop outcomes become more sensitive to shocks. Diversification of habitats and reduced chemical pressure can act like an insurance policy against yield variability.
- Use public-facing rankings for education. Top-100 country lists are powerful for media, schools, and local initiatives, as long as uncertainty and documentation gaps are communicated clearly.
Human angle: why rankings can trigger real-world action
Pollinators are unusually well-suited for broad public engagement because the solutions are visible and local: flower-rich margins, reduced mowing, pesticide risk reduction, and urban habitat corridors. In many countries, “bee-friendly” initiatives have become a bridge between agriculture and biodiversity: they allow farmers, municipalities, schools, and households to participate in measurable improvements without needing to wait for multi-year infrastructure programmes.
A useful way to read the Top 100 list is as a map of where biodiversity potential is high (hotspots) and where information is thin (data gaps). Both point to priorities: conservation in the first case, capacity-building and surveys in the second.
Primary data sources and technical notes
-
IPBES assessment on pollinators and pollination — synthesis of global evidence on pollinator importance, pressures, and policy options (summary for policymakers).
https://files.ipbes.net/ipbes-web-prod-public-files/spm_deliverable_3a_pollination_20170222.pdf -
Map of Life: Butterfly Country Checklists — country-level occurrences compiled from literature and GBIF, harmonised to a master taxonomy.
https://mapoflife.ai/documentation/butterfly-country-checklists -
Discover Life: bee species guide & world checklist — widely used global reference for wild bee taxonomy and country presence signals (metadata and entry points).
https://www.discoverlife.org/mp/20q?act=x_checklist&guide=Apoidea_species -
GBIF (Global Biodiversity Information Facility) — open infrastructure for biodiversity occurrence records used in many checklist products and harmonisations.
https://www.gbif.org/ -
World Bank WDI: Agricultural land (% of land area) — proxy indicator used here to illustrate land-use pressure context.
https://data.worldbank.org/indicator/AG.LND.AGRI.ZS
Method note: totals in this article represent documented bee and butterfly species per country (≈), rounded and harmonised for cross-country comparability. Due to uneven sampling and ongoing taxonomy updates, ranks and counts should be interpreted as an analytical snapshot for 2025.
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Asset pack for: Top 100 Countries by Pollinator Diversity (Bees and Butterflies), 2025
