king_2026_biodiversity_woodland

46,197 rated or chosen profiles from 1,711 respondents, in up to 9 tasks of 3 profiles varying on 5 attributes.

About this table

DescriptionChoice experiment on the management of a new woodland in Great Britain (winter wave): 1,711 adults chose in nine tasks among Option A, Option B and No change, described by the variety of sounds, colours and smells, the amount of deadwood and a yearly council tax increase.
ReferenceKing, P., Davies, Z., et al. (2026). Replication materials: Stated preferences for the colours, smells, and sounds of biodiversity [Data set]. Zenodo.
DOI10.1016/j.ecolecon.2024.108410
LicenceMIT License
Source datahttps://doi.org/10.5281/zenodo.20645896

Notes

These notes describe the source data, which the IRW reproduces as released. All notes are listed on the Data Notes page.

Size and shape

Respondents1,711
Rows (one per respondent, task and profile)46,197
Tasks per respondent (most)9
Profiles per task3
Attributes5
Tasks with no profile chosen0

Design

Topicclimate energy environment
A profile representspolicy
CountryGB
Language shownen
Language of stored levelsen
Randomization restrictionsunknown
Task orderrecorded in the deposit
Profile positionrecorded in the deposit

Outcomes:

choiceWhich ONE of the above choices would you pick for the new woodland? (Option A / Option B / No change) [choice, forced]

Columns

attr_colour_varietyattr_council_tax_increaseattr_deadwoodattr_smell_varietyattr_sound_varietychoicecov_age_groupcov_areacov_countrycov_educationcov_household_incomeidprofiletasktrial_block

The layout (one row per respondent, task and profile; choice/rating outcomes; attr_ columns holding each attribute level as displayed) is defined in the IRW conjoint standard. What the outcomes asked is under Design above.

Get the data

Download CSVno account neededBrowse on Redivisexplore and queryCroissant metadataHugging Face, Kaggle, OpenML

Or load it directly in R or Python (both need a free Redivis account; the first call opens a browser to sign in):

# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("king_2026_biodiversity_woodland", source = "conj")
# Python
pip install irw

import irw
df = irw.fetch("king_2026_biodiversity_woodland", source="conj")

How to cite

@article{King_2025, title={Stated preferences for the colours, smells, and sounds of biodiversity}, volume={227}, ISSN={0921-8009}, url={http://dx.doi.org/10.1016/j.ecolecon.2024.108410}, DOI={10.1016/j.ecolecon.2024.108410}, journal={Ecological Economics}, publisher={Elsevier BV}, author={King, Peter M. and Dallimer, Martin and Lundhede, Thomas and Austen, Gail E. and Fisher, Jessica C. and Irvine, Katherine N. and Fish, Robert D. and Davies, Zoe G.}, year={2025}, month=Jan, pages={108410} }

Version and provenance

IRW versionv584
Redivis datasetirw_conjoint_2 v1.4
Redivis dataset DOI10.57761/hk97-wv30
Manifest pin for this IRW versionv1.4
Metadata sourceirw_meta v44.0