Cacti can survive in the harshest environments, and yet almost a third of species are threatened with extinction.
Photo Credit: Haoli Chen
Scientific Frontline: Extended "At a Glance" Summary: CactEcoDB Database
The Core Concept: CactEcoDB is a comprehensive, open-access ecological and evolutionary database encompassing over 1,000 species within the cactus family (Cactaceae). It centralizes critical biodiversity data to assist researchers and conservationists in safeguarding these highly threatened plants.
Key Distinction/Mechanism: Prior to this database, data concerning cactus ecology and evolution was fragmented and difficult to access. CactEcoDB distinguishes itself by integrating previously dispersed global data into a singular, curated platform that standardizes biological traits, geographic range maps, and evolutionary timelines.
Origin/History: Launched in March 2026 by researchers from the Universities of Bath and Reading, the database is the culmination of seven years of data collection and compilation. The findings and the dataset were published in Scientific Data and hosted on Figshare.
Major Frameworks/Components:
- Curated Geographic Range Maps: Expert-verified geographical distributions based on International Union for Conservation of Nature (IUCN) assessments.
- Environmental and Climate Data: Detailed tracking of arid climate variability, including rainfall patterns, temperature fluctuations, and soil sand content.
- Key Biological Traits: Standardized categorizations of growth forms, height, and pollination strategies.
- Evolutionary Phylogeny: The largest time-calibrated evolutionary family tree constructed for cacti species.
- Speciation Metrics: Detailed tracking of species-level diversification and speciation rates.
Branch of Science: Botany, Conservation Biology, Ecology, and Evolutionary Biology
Future Application: The database is designed to serve as a foundational tool for integrating artificial intelligence and machine learning into ecological studies. Because individual cactus groups face unique climatic challenges, AI could utilize this dataset to formulate specialized conservation and cultivation strategies specific to different arid environments.
Why It Matters: Cacti possess extreme adaptations to harsh environments, yet they are among the most threatened plant families on Earth, with 31% of the roughly 1,850 species currently at risk of extinction. By centralizing vital ecological data, CactEcoDB accelerates critical research needed to combat existential threats from habitat loss, climate change, and illegal trade.
With almost a third of cacti species threatened with extinction, researchers from the Universities of Bath and Reading have launched CactEcoDB, the most comprehensive database ever created for the cactus family, offering an unprecedented window into the evolution, ecology and conservation needs of one of the world’s most distinctive and endangered groups of plants.
Cactaceae - the family that includes everything from tiny globular cacti to towering desert giants - comprises around 1,850 species found across the Americas.
Cacti are famous for their extreme adaptations to water scarcity and harsh environments, but they are also under severe threat: 31% of species are currently at risk of extinction, with habitat loss, climate change and illegal trade putting many more in danger.
To help scientists better understand and protect these unique plants, the team behind CactEcoDB assembled an open access dataset drawing on hundreds of data sources collected over seven years and covering more than 1,000 cactus species.
Dr Jamie Thompson, Leverhulme Research Fellow from the University of Reading and first author of the paper, said: “Unlike for many animal groups, there was no central curated database of cactus biodiversity until now.
“The data needed to understand their conservation, ecology and evolution have been fragmented, incomplete and difficult for researchers to access. Our database fills this critical gap and could be a powerful tool for studying diversity.”
Dr Nick Priest, from the University of Bath’s Department of Life Sciences and the Centre for Artificial Intelligence, said: "Cacti capture our imagination as icons of endurance and survivors of the planet's inhospitable environments, and yet they are amongst the most threatened plant families on Earth – even the giant saguaro cacti are collapsing in the Arizona summer heat.
“By bringing together this wealth of information in one place, we hope to enable new research that can ultimately support their conservation.”
The new dataset greatly expands on earlier work, offering improved trait coverage, more refined growth‑form categories, expert‑verified range maps based on IUCN assessments, and the most complete phylogeny to date.
By making the resource freely available, the authors hope to support future research, especially studies integrating machine learning in the ecology, evolution and conservation of cacti. They invite the scientific community to contribute additional data as it becomes available.
One of the striking features of the database is the variability of arid climates, especially in rainfall patterns, temperature fluctuations, and sand content in soil.
Dr Thompson said: "It's climatic variability that makes deserts such hostile places to live. But the data is telling us that each group of cacti faces different climatic challenges."
This body of information is bound to be of interest to a range of people, including cactus enthusiasts, cultivators and conservationists.
"But, because no two deserts are alike, it is going to be tricky working out general rules for how to protect cacti from climate change," says Dr Priest. "AI could be our best hope of finding conservation strategies specific to each major group of cacti."
Research material: Cactus Ecological Database
Published in journal: Scientific Data
Authors: Jamie B. Thompson, Catherine Martinez, Jorge Avaria-Llautureo, Santiago Ramírez-Barahona, Gerardo Manzanarez-Villasana, Alastair Culham, Andrew Gdaniec, George Ryan, Chris Venditti, Georgia Keeling, and Nicholas K. Priest
Source/Credit: Universities of Bath
Reference Number: bot032626_01
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