O esterco longe de quem aduba: Onde há mais boi por km², menos estabelecimentos usam adubo orgânico

Cerejo, Lucas Nakamura

No. 114 Energy · biomass Bioenergy, crossed 4/5

Manure far from who spreads it

Where there are more cattle per km², fewer farms use organic fertiliser

Record, downloads and citation

Bivariate map of São Paulo’s municipalities in nine colours, crossing thirds of cattle per km² (light to ochre) with thirds of the share of holdings using organic fertiliser (light to lilac). The ochre of many cattle and little fertiliser covers the west and north-west, from the Pontal to São José do Rio Preto; the lilac of few cattle and much fertiliser, the capital’s surroundings, the Ribeira Valley and the Upper Tietê; the brown of much of both, the Paraíba Valley. The 28 municipalities without data, nearly all in Greater São Paulo and on the coast, are hatched. Callouts point to Ferraz de Vasconcelos, with 81% of holdings using organic fertiliser, and Presidente Bernardes, with 202 cattle per km² and 16%. In the panel, the 3 × 3 grid and the table of correlations. — Fig. 114 São Paulo State (SP) EPSG:4674 Source: IBGE

Where there are more cattle per km², fewer farm holdings use organic fertiliser. Across the 617 São Paulo municipalities with data, the rank correlation between the 2024 cattle herd and the share of holdings that applied organic fertiliser in the 2017 Agricultural Census is −0.41, and −0.32 net of urbanisation, density and income. In the quarter of municipalities with fewest cattle, the median is 32%; in the quarter with most, 18%. Grazing cattle leave their manure on pasture, and organic fertiliser includes compost from market gardens near towns: Ferraz de Vasconcelos, with 2.2 cattle per km², has 81%; Presidente Bernardes, with 202, 16%. Fourth plate of the collection “Bioenergy, crossed”.

Technical record · downloads · citation

At a glance

Layers

municipios polygon 645 municipalities with the variables of all five plates, the bivariate classes and the LISA clusters (same GPKG as plates 111 to 115)
gasodutos line Gas transmission pipelines and distribution network (EPE)
regioes_intermediarias polygon 11 intermediate geographic regions
limite_estadual polygon State boundary

Metadata

Sources: IBGE — Municipal Livestock Survey (PPM) 2024, table 3939: herd size (2024)
IBGE — 2017 Agricultural Census, SIDRA table 6847 (holdings by use of fertiliser) (2017)
IBGE — 2022 Population Census (population, urbanisation and income by municipality) (2022)
IBGE — Municipal Mesh 2025 (2025)
Extent: São Paulo State (SP)
CRS / Projection: SIRGAS 2000 (EPSG:4674)
EPSG:4674
Software: Node.js · d3-geo · QGIS
Method: Cattle per km² (IBGE, PPM 2024) and share of farm holdings that applied organic fertiliser, alone or with chemical (IBGE, 2017 Agricultural Census), each in thirds of municipalities, crossed in a 3 × 3 bivariate map; Spearman rank correlations, raw and partial, and bivariate LISA.
Version: v1.0.0
Licence: CC BY 4.0
DOI: being registered on Zenodo

Downloads

Figure to reuse

The map without a frame, with legend, scale, reference system and credit written on it: ready for papers, lectures and slides. In two versions: with the basemap (neighbours and sea) or only the mapped area, on white.

With basemap (PNG) Without basemap (PNG) QR code (SVG)

Point a camera at it to open this page.

How to cite

Cerejo, L. N. (2026). O esterco longe de quem aduba: onde há mais boi por km², menos estabelecimentos usam adubo orgânico [Manure far from who spreads it: Where there are more cattle per km², fewer farms use organic fertiliser] (Version 1.0.0) [Data set]. Essencial. https://aikiesan.github.io/essencial-geo/en/maps/114-esterco-longe-de-quem-aduba-sp/

@dataset{cerejo2026_esterco_longe_de_quem_aduba_sp,
  author    = {Cerejo, Lucas Nakamura},
  title     = {O esterco longe de quem aduba: Onde há mais boi por km², menos estabelecimentos usam adubo orgânico},
  year      = {2026},
  publisher = {Essencial},
  version   = {1.0.0},
  url       = {https://aikiesan.github.io/essencial-geo/en/maps/114-esterco-longe-de-quem-aduba-sp/},
  language  = {portuguese},
  note      = {English title: Manure far from who spreads it: Where there are more cattle per km², fewer farms use organic fertiliser. Licence CC BY 4.0}
}

How to read this plate area, projection, scale, legend and source · 1 terms

1 Area: São Paulo State (SP) The area the plate covers. Outside it, neighbours and sea are drawn in grey, just for orientation.
2 Coordinates and projection: SIRGAS 2000 (EPSG:4674) The layers are in SIRGAS 2000; the drawing’s projection is written in the colophon at the foot of the panel.
3 Scale: Graphic scale bar in the panel The scale bar is true on the central meridian; away from it, measured distances vary a little.
4 Legend and layers: 4 layers in the GeoPackage · polygon, line Read the legend before the map: it tells you whether a colour is a rate or a class, and whether a circle is a total.
5 Sources: IBGE (2024); IBGE (2017); IBGE (2022); IBGE (2025) Every figure comes from a public source, with its year. The data sheet gives each one’s address.

Terms on this plate

2022 Census: IBGE’s door-to-door count. Results by census tract give residents, age, household-head income, water, sewerage and rubbish.

Anatomy of a plate Full glossary

Download

Layers, table and figures, under CC BY 4.0. Cite with the DOI.

Full record and citation

Method notes · No. 114

Cattle per km² and holdings using organic fertiliser across São Paulo’s municipalities

Português · English

Plate No. 114, the fourth of five in the collection Bioenergy, crossed; the previous one is plate 113; the next, plate 115.

The collection crosses São Paulo’s bioenergy with what filling stations sell, with the countryside and with town halls, across the state’s 645 municipalities. The pairs came from a correlation screen between CP2B biomethane potential, fuel sales in the SEMIL Yearbook, plantation forestry, the cattle herd, the Agricultural Census, the vehicle fleet and MUNIC. Each pair went through raw and partial rank correlation (net of urbanisation, density and income), an effective sample corrected for spatial autocorrelation, Benjamini–Hochberg q values and bivariate LISA. The last plate is descriptive, with no test, and the text says so.

The map’s callouts point to Ferraz de Vasconcelos, in the metropolitan market-garden belt, where 81% of holdings used organic fertiliser with 2.2 cattle per km², and Presidente Bernardes, in the Pontal, with 202 cattle per km² and 16%: one of the 136 municipalities with little fertiliser surrounded by many cattle.

What the files contain

Layer (GPKG)	Geometry	Content
`municipios`	polygon	645 municipalities with cane and ethanol, biomethane and diesel, the fleet, native cover and pulpwood, cattle and organic fertiliser, distances to the pipeline, piped gas and the MUNIC answers on waste; classes `b111`, `b113`, `b114`, `arranjo115` and clusters `lisa111`, `lisa113`, `lisa114`
`gasodutos`	line	transmission pipelines and distribution network (`tipo`)
`regioes_intermediarias`, `limite_estadual`	polygon	reference

The GPKG is the same for all five plates and carries a QGIS style for each. The CSV has the municipal table, without geometry. Empty fields are missing data, not zero. LISA clusters come as AA (high-high), BB (low-low), AB, BA and ns (not significant); the first letter is the municipality’s variable, the second its neighbours’.

Method

bovinos_km2: cattle herd on 31/12/2024 (IBGE, PPM, table 3939) over municipal area.
estab_agro, estab_adubo_organico and pct_estab_adubo_organico: farm holdings, those that applied organic or chemical-and-organic fertiliser, and the share, in % (IBGE, 2017 Agricultural Census, SIDRA 6847).
Thirds of cattle: up to 22.0, 22.0 to 59.7 and over 59.7 head per km²; of organic fertiliser: up to 20.1%, 20.1% to 33.3% and over 33.3%. b114: bivariate class, tens = third of cattle (1 to 3), units = third of organic fertiliser (1 to 3). From bottom to top and left to right, the nine cells hold 37, 54, 114; 70, 77, 58; 98, 75, 34 municipalities. Statewide, 28.7% of holdings used organic fertiliser; 28 municipalities have no data, nearly all in Greater São Paulo and on the coast: PPM publishes no cattle herd for them, and for some the Agricultural Census has no data either. Missing data is not zero.
n_kg_ha_agro: nitrogen in livestock manure per hectare of farmland (plate 081). By quarters of nitrogen, the median share of organic fertiliser falls from 30.8% to 21.6%.
Organic fertiliser × cattle per km² (log): Spearman rank correlation −0.41 (617 municipalities), partial −0.32, effective sample 351, p < 0.001, q < 0.001. lisa114: bivariate LISA clusters (organic fertiliser in the municipality × cattle in its neighbours): 46 high-high, 62 low-low, 113 high-low and 136 low-high; bivariate Moran’s I −0.39. Low-high by intermediate region: São José do Rio Preto (50), Presidente Prudente (36) and Araçatuba (26).
Partial correlation: the correlation between the residuals of each variable’s ranks regressed on the ranks of the controls, which are urbanisation (residents in urban areas), log of population density and log of income per head (2022 Census). Effective sample under spatial autocorrelation: n·(1 − Iₓ·Iᵧ)/(1 + Iₓ·Iᵧ), where Iₓ and Iᵧ are the Moran’s I of the residuals over a 6-nearest-neighbour neighbourhood; Benjamini–Hochberg q values across all pairs in the screen. Bivariate LISA: the municipality’s value against the mean of its 6 neighbours on the other variable, 999 permutations, seed 20261019, p < 0.05.

Limitations

The Agricultural Census dates from 2017 and the herd from 2024: seven years separate the two measures.
Organic fertiliser is not only manure: it includes compost and other residues, and the Census counts holdings, not tonnes or hectares. Pasture is rarely fertilised, and manure from grazing cattle stays in the field, uncollected; the map shows where manure exists and where it is used as fertiliser, not how much of it is lost.
Ecological reading: the map compares municipalities, not people or farms. A correlation between municipalities does not say that the same farms or drivers have both traits, nor that one causes the other.

View this map’s folder on GitHub