PEVS

Overview

PEVS (Produção da Silvicultura e da Extração Vegetal - Silviculture and Forestry Extraction Production) is a comprehensive annual survey conducted by IBGE that collects data on forestry and related activities in Brazil.

This dataset provides:

PEVS is Brazil’s primary source for forestry production statistics, important for understanding the timber industry, forest management practices, and sustainable use of forest resources.

Data Source and Coverage

PEVS data comes from: - Direct surveys of forestry companies and producers - Administrative records from forestry operations - Compiled and validated by IBGE’s agriculture statistics division - Annual release with data for previous year - Covers both industrial and subsistence-level forestry activities

For more information, visit IBGE Agriculture Statistics.

Available Datasets

1. pevs_forest_crops

Production data from forest crop plantations (timber and non-timber products).

2. pevs_silviculture

Data on silviculture activities including afforestation, reforestation, and forest management.

3. pevs_silviculture_area

Total existing area used for silviculture operations, disaggregated by forest species.

Function Parameters

1. dataset

Selects which forestry dataset to download.

dataset = "pevs_forest_crops"       # Forest crop production (1986-2019)
dataset = "pevs_silviculture"       # Silviculture production (1986-2019)
dataset = "pevs_silviculture_area"  # Silviculture land area (2013-2019)

2. raw_data

Controls whether to download original or processed data.

raw_data = FALSE  # logical

3. geo_level

Specifies the geographic aggregation level.

geo_level = "state"  # character string

4. time_period

Defines which year(s) to download.

Important: Dataset-specific availability:

Dataset Available Years
pevs_forest_crops 1986-2019
pevs_silviculture 1986-2019
pevs_silviculture_area 2013-2019 
time_period = 2019              # single year
time_period = c(2010, 2015)     # specific years
time_period = 2010:2019         # range of years

5. language

Output language for variable names.

language = "eng"  # character string

Examples

Example 1: Forest crop production by state

# download treated forest crops data at the state level for 2019
forest_crops <- load_pevs(
  dataset = "pevs_forest_crops",
  raw_data = FALSE,
  geo_level = "state",
  time_period = 2019,
  language = "eng"
)

Example 2: Silviculture area by state over time

# download treated silviculture area data at the state level for 2013 to 2019
silvi_area <- load_pevs(
  dataset = "pevs_silviculture_area",
  raw_data = FALSE,
  geo_level = "state",
  time_period = 2013:2019,
  language = "eng"
)

Example 3: Silviculture production by region

# download treated silviculture production data at the region level for 2019
silvi_prod <- load_pevs(
  dataset = "pevs_silviculture",
  raw_data = FALSE,
  geo_level = "region",
  time_period = 2019,
  language = "eng"
)

Data Notes

Data Structure

Each row typically represents: - A geographic unit (country, region, state, or municipality) - A specific year - A product type or forest species - Quantity produced (in appropriate units: cubic meters, tons, etc.) - Value of production (in currency units)

Product Categories

Forest crops include: - Timber species: Eucalyptus, pine, other timber - Non-timber products: Charcoal, resins, turpentine, cork, bark - Other forest products: Tannin, rosin, pulpwood

Exact categories vary by dataset and year.

Raw vs. Treated Data

Important Limitations

  1. Data collection changes: Survey methodology may evolve over time
  2. Area vs. production: Area data only available from 2013; earlier years have production data only
  3. Municipality data sparse: Many small municipalities may have zero or no reported data
  4. Seasonal nature: Some products are seasonal; annual aggregates smooth out variation
  5. Informal forestry: May undercount small-scale or informal forestry operations

Units of Measurement